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VeröffentlichungsnummerCN102096717 A
PublikationstypAnmeldung
AnmeldenummerCN 201110038433
Veröffentlichungsdatum15. Juni 2011
Eingetragen15. Febr. 2011
Prioritätsdatum15. Febr. 2011
Auch veröffentlicht unterCN102096717B
Veröffentlichungsnummer201110038433.2, CN 102096717 A, CN 102096717A, CN 201110038433, CN-A-102096717, CN102096717 A, CN102096717A, CN201110038433, CN201110038433.2
Erfinder刘建柱
Antragsteller百度在线网络技术(北京)有限公司
Zitat exportierenBiBTeX, EndNote, RefMan
Externe Links:  SIPO, Espacenet
Search method and search engine
CN 102096717 A
Zusammenfassung
The invention provides a search method. The search method comprises the following steps of: S1, receiving a query command; S2, performing demand intention analysis on the query command based on a knowledge base, and defining the demand intention of the query command; S3, searching the query command carrying the demand intention in a database to obtain a search result; and S4, outputting the search result. Compared with the prior art, the search method has the advantages that: on the basis of the knowledge base, the query command input by a user is understood better; the intention of the query command is analyzed; the structure of the query command is analyzed to perform semantic content expansion on the query command so as to better guide a search engine to select quality resources to meet the search requirements on the user; therefore, the search efficiency of the user is improved and the network traffic is saved.
Ansprüche(28)  übersetzt aus folgender Sprache: Chinesisch
1. 一种搜索方法,其特征在于,所述搜索方法包括以下步骤:S1、接收查询指令;S2、基于知识库对所述查询指令进行需求意图分析,明确所述查询指令的需求意图;S3、将带有需求意图的所述查询指令在数据库中搜索,得到搜索结果;S4、输出所述搜索结果。 A search method, wherein the method comprises the steps of the search: S1, receiving a query command; S2, based on knowledge of the intention of the query instructions demand analysis, demand a clear intention of the query command; S3 the intent of the query command with demand search the database to obtain search results; S4, the output of the search results.
2.根据权利要求1所述的搜索方法,其特征在于,所述数据库为网页存储库或与所述需求意图相对应的垂直搜索数据库。 2. The search method according to claim 1, characterized in that the database is a repository or web page with the intention of demand corresponding vertical search database.
3.根据权利要求1所述的搜索方法,其特征在于,在所述S2步骤和S3步骤间,还包括语义扩充步骤:基于所述知识库对所述查询指令进行语义扩充。 3. The search method according to claim 1, characterized in that, between step S2 and the step S3, further comprising the step of semantic expansion: based on the knowledge of the semantic query expansion instruction.
4.根据权利要求1所述的搜索方法,其特征在于,所述“基于知识库对所述查询指令进行需求意图分析,明确所述查询指令的需求意图”具体包括以下流程:S200、通过用户历史行为库给知识库中的各个知识片段的各个需求意图打分,使各个知识片段都具有相应的需求意图得分;S201、将所述查询指令与知识片段匹配,得到与所述查询指令相匹配的至少一个知识片段;S202、将与所述查询指令相匹配的知识片段的需求意图得分加总,得到第一分数;S203、通过与所述查询指令相匹配的知识片段在所述知识库中的从属关系,加减所述第一分数,得到知识库整体需求得分;S204、判断所述知识库整体需求得分是否大于一设定阈值;S205、若大于所述设定阈值,则以所述知识库整体需求得分最高的需求类型作为所述查询指令的需求意图;S206、若小于所述设定阈值,则判断所述查询指令无明显需求意图。 4. The search method according to claim 1, characterized in that said "Knowledge based on the intention to analyze the needs of the query instructions, clear intent of the query command needs" specifically includes the following processes: S200, user historical behavior to the individual needs of the library repository of knowledge in the various segments of intent scoring, so that all pieces of knowledge has a corresponding demand intention score; S201, the query instruction and match pieces of knowledge to give instructions to the query matches knowledge of at least one segment; S202, the intention of the query command needs to match the pieces of knowledge scores are summed to obtain a first fraction; S203, with the instruction that matches the query fragments of knowledge in the knowledge base affiliation, subtraction of the first score, the score obtained knowledge overall demand; S204, determines the overall demand knowledge score is greater than a predetermined threshold; S205, if greater than the predetermined threshold, places the knowledge Library overall demand for the highest score, as the demand for the type of query command needs intention; S206, if less than the set threshold value, it is determined no significant demand for the query command intent.
5.根据权利要求1所述的搜索方法,其特征在于,所述“基于知识库对所述查询指令进行需求意图分析,明确所述查询指令的需求意图”具体包括以下流程:S200、通过用户历史行为库给知识库中的各个知识片段的各个需求意图打分,使各个知识片段都具有相应的需求意图得分;S201、将所述查询指令与知识片段和表达模板匹配,得到与所述查询指令相匹配的至少一个知识片段和一表达模板;S202、将与所述查询指令相匹配的知识片段的需求意图得分加总,得到第一分数;S203、通过与所述查询指令相匹配的知识片段在所述知识库中的从属关系,加减所述第一分数,得到知识库整体需求得分;S204、对所述查询指令在表达模板层面上进行打分,得到表达模板得分;S205、将知识库整体需求得分与表达模板得分的加权之和作为查询指令需求强度得分;S206、判断所述查询指令需求强度得分是否大于一设定阈值;S207、若大于所述设定阈值,则以查询指令需求强度得分最高的需求类型作为所述查询指令的需求意图;S208、若小于所述设定阈值,则判断所述查询指令无明显需求意图。 5. The search method according to claim 1, characterized in that the "knowledge base based on the intention to analyze the needs of the query instructions, clear intent of the query command needs" specifically includes the following processes: S200, user historical behavior to the individual needs of the library repository of knowledge in the various segments of intent scoring, so that all pieces of knowledge has a corresponding demand intention score; S201, the query commands and pieces of knowledge and expression template matching, get to the query command match fragments and a knowledge of at least one expression templates; S202, the intention of the query command needs to match the pieces of knowledge scores are summed to obtain a first fraction; S203, through knowledge fragments that match the query instructions affiliation in the Knowledge Base, plus or minus the first score, the score to give the overall demand for knowledge; S204, for instruction in the query expression of scoring on the template level, to give expression template score; S205, the knowledge base overall demand scores and expression templates weighted sum of scores as the query command needs strength score; S206, determining whether the query command needs strength score is greater than a predetermined threshold; S207, if greater than the predetermined threshold, places query command needs the strength of demand for the highest score type as the query command needs intention; S208, if less than the set threshold value, it is determined that no significant demand for the query command intent.
6. 一种搜索方法,其特征在于,所述搜索方法包括以下步骤:51、接收查询指令;52、基于知识库对所述查询指令进行需求意图分析,明确所述查询指令的需求意图,同时,基于所述知识库对所述查询指令进行语义扩充;53、将带有需求意图并扩充语义的查询指令在数据库中搜索,得到搜索结果;54、输出所述搜索结果。 A search method, characterized in that the method comprises the steps of searching: 51, receiving a query instruction; 52, based on knowledge of the intention to analyze the needs of the query instructions, clear intent of the query command needs, while based on the knowledge of the semantic query expansion instruction; 53, will expand with the demand and the semantics of the query intent instruction search the database to obtain search results; 54, the output of the search results.
7.根据权利要求6所述的搜索方法,其特征在于,所述数据库为网页存储库或与所述需求意图相对应的垂直搜索数据库。 7. The search method according to claim 6, characterized in that said web repository or database with the intention of demand corresponding vertical search database.
8.根据权利要求6所述的搜索方法,其特征在于,所述“基于知识库对所述查询指令进行需求意图分析,明确所述查询指令的需求意图”具体包括以下流程:5200、通过用户历史行为库给知识库中的各个知识片段的各个需求意图打分,使各个知识片段都具有相应的需求意图得分;5201、将所述查询指令与知识片段匹配,得到与所述查询指令相匹配的至少一个知识片段;5202、将与所述查询指令相匹配的知识片段的需求意图得分加总,得到第一分数;5203、通过与所述查询指令相匹配的知识片段在所述知识库中的从属关系,加减所述第一分数,得到知识库整体需求得分;5204、判断所述知识库整体需求得分是否大于一设定阈值;5205、若大于所述设定阈值,则以所述知识库整体需求得分最高的需求类型作为所述查询指令的需求意图;5206、若小于所述设定阈值,则判断所述查询指令无明显需求意图。 8. The search method according to claim 6, characterized in that the "knowledge base based on the intention to analyze the needs of the query instructions, clear intent of the query command needs" specifically includes the following processes: 5200, by the user historical behavior to the individual needs of the library repository of knowledge in the various segments of intent scoring, so that all pieces of knowledge has a corresponding demand intention score; 5201, the fragments match the query instruction and knowledge to give instructions to the query matches knowledge of at least one fragment; 5202, with the intention to demand that match the query instructions knowledge fragments score summed to obtain a first fraction; 5203, with the instruction that matches the query fragments of knowledge in the knowledge base affiliation, subtraction of the first score, the score obtained knowledge overall demand; 5204, determines the overall demand knowledge score is greater than a predetermined threshold; 5205, if greater than the predetermined threshold, places the knowledge Library overall demand for the highest score, as the demand for the type of query command intent requirement; 5206, if less than the set threshold value, it is determined no significant demand for the query command intent.
9.根据权利要求6所述的搜索方法,其特征在于,所述“基于知识库对所述查询指令进行需求意图分析,明确所述查询指令的需求意图”具体包括以下流程:5200、通过用户历史行为库给知识库中的各个知识片段的各个需求意图打分,使各个知识片段都具有相应的需求意图得分;5201、将所述查询指令与知识片段和表达模板匹配,得到与所述查询指令相匹配的至少一个知识片段和一表达模板;5202、将与所述查询指令相匹配的知识片段的需求意图得分加总,得到第一分数;5203、通过与所述查询指令相匹配的知识片段在所述知识库中的从属关系,加减所述第一分数,得到知识库整体需求得分;5204、对所述查询指令在表达模板层面上进行打分,得到表达模板得分;5205、将知识库整体需求得分与表达模板得分的加权之和作为查询指令需求强度得分;5206、判断所述查询指令需求强度得分是否大于一设定阈值;5207、若大于所述设定阈值,则以查询指令需求强度得分最高的需求类型作为所述查询指令的需求意图;5208、若小于所述设定阈值,则判断所述查询指令无明显需求意图。 9. The search method according to claim 6, characterized in that the "knowledge base based on the intention to analyze the needs of the query instructions, clear intent of the query command needs" specifically includes the following processes: 5200, by the user historical behavior to the individual needs of the library repository of knowledge in the various segments of intent scoring, so that all pieces of knowledge has a corresponding demand intention score; 5201, the query commands and pieces of knowledge and expression template matching, get to the query command match fragments and a knowledge of at least one expression templates; 5202, with the intention to demand that match the query instructions knowledge fragments score summed to obtain a first fraction; 5203, through knowledge fragments that match the query instructions affiliation in the Knowledge Base, plus or minus the first score, the score to give the overall demand for knowledge; 5204, for the query expression scoring instructions on the template level, to give expression template score; 5205, the Knowledge Base overall demand scores and expression templates weighted sum of scores as the query command needs strength score; 5206, judges score the query command the strength of demand is greater than a predetermined threshold; 5207, if greater than the predetermined threshold, places query command needs the strength of demand for the highest score type as the query command intent requirement; 5208, if less than the set threshold value, it is determined that no significant demand for the query command intent.
10. 一种搜索方法,其特征在于,所述搜索方法包括以下步骤:Si、接收查询指令;.52、基于知识库和表达模板库对所述查询指令进行需求意图分析,明确所述查询指令的需求意图;.53、将带有需求意图的所述查询指令在数据库中搜索,得到搜索结果;.54、输出所述搜索结果。 10. A search method, wherein the method comprises the steps of the search: Si, receiving a query command; .52, based on knowledge and expression template library for the query instructions intention demand analysis, clear the query command demand intent; .53, the query instruction intent with demand search the database to obtain search results; .54, the output of the search results.
11.根据权利要求10所述的搜索方法,其特征在于,所述数据库为网页存储库或与所述需求意图相对应的垂直搜索数据库。 11. The search method according to claim 10, wherein said database is a repository or web page with the intention of demand corresponding vertical search database.
12.根据权利要求10所述的搜索方法,其特征在于,在所述S2步骤和S3步骤间,还包括语义扩充步骤:基于所述知识库对所述查询指令进行语义扩充。 12. The search method according to claim 10, characterized in that, between step S2 and the step S3, further comprising the step of semantic expansion: based on the knowledge of the semantic query expansion instruction.
13.根据权利要求10所述的搜索方法,其特征在于,所述“基于知识库对所述查询指令进行需求意图分析,明确所述查询指令的需求意图”具体包括以下流程:.5200、通过用户历史行为库给知识库中的各个知识片段的各个需求意图打分,使各个知识片段都具有相应的需求意图得分;.5201、将所述查询指令与知识片段匹配,得到与所述查询指令相匹配的至少一个知识片段;.5202、将与所述查询指令相匹配的知识片段的需求意图得分加总,得到第一分数;.5203、通过与所述查询指令相匹配的知识片段在所述知识库中的从属关系,加减所述第一分数,得到知识库整体需求得分;.5204、判断所述知识库整体需求得分是否大于一设定阈值;.5205、若大于所述设定阈值,则以所述知识库整体需求得分最高的需求类型作为所述查询指令的需求意图;.5206、若小于所述设定阈值,则判断所述查询指令无明显需求意图。 13. The search method according to claim 10, characterized in that said "Knowledge-based query instructions on the intent requirement analysis needs clear intent of the query command," specifically includes the following processes: .5200 by user behavior history database to individual requirements of each knowledge fragment Knowledge intent scoring, so that all pieces of knowledge has a corresponding demand intention score; .5201, the query instruction and knowledge fragment match to give instructions with respect to the query match at least one of pieces of knowledge; .5202, with the intention to demand that match the query instructions knowledge fragments score summed to obtain a first fraction; .5203, with the instruction that matches the query fragment in the knowledge affiliation Knowledge Base, plus or minus the first score, the overall demand for knowledge score obtained; .5204, the overall demand for judging the knowledge base score is greater than a predetermined threshold; .5205, if greater than the predetermined threshold , places the highest score overall demand for knowledge requirement type as the query command intent requirement; .5206, if less than the set threshold value, it is determined that no significant demand for the query command intent.
14.根据权利要求10所述的搜索方法,其特征在于,所述“基于知识库对所述查询指令进行需求意图分析,明确所述查询指令的需求意图”具体包括以下流程:.5200、通过用户历史行为库给知识库中的各个知识片段的各个需求意图打分,使各个知识片段都具有相应的需求意图得分;.5201、将所述查询指令与知识片段和表达模板匹配,得到与所述查询指令相匹配的至少一个知识片段和一表达模板;.5202、将与所述查询指令相匹配的知识片段的需求意图得分加总,得到第一分数;.5203、通过与所述查询指令相匹配的知识片段在所述知识库中的从属关系,加减所述第一分数,得到知识库整体需求得分;.5204、对所述查询指令在表达模板层面上进行打分,得到表达模板得分;.5205、将知识库整体需求得分与表达模板得分的加权之和作为查询指令需求强度得分;.5206、判断所述查询指令需求强度得分是否大于一设定阈值;.5207、若大于所述设定阈值,则以查询指令需求强度得分最高的需求类型作为所述查询指令的需求意图;.5208、若小于所述设定阈值,则判断所述查询指令无明显需求意图。 14. The search method according to claim 10, characterized in that said "Knowledge-based query instructions on the intent requirement analysis needs clear intent of the query command," specifically includes the following processes: .5200 by user behavior history database to individual requirements of each knowledge fragment Knowledge intent scoring, so that all pieces of knowledge has a corresponding demand intention score; .5201, the query commands and pieces of knowledge and expression template matching, and get the query command match fragments and a knowledge of at least one expression templates; .5202, with the intention to demand that match the query instructions knowledge fragments score summed to obtain a first fraction; .5203, through to the query command phase matching pieces of knowledge affiliation in the Knowledge Base, plus or minus the first score, the score to give the overall demand for knowledge; .5204, for instruction in the query expression of scoring on the template level, to give expression template score; .5205, the overall demand for knowledge and expression templates score score weighted sum of the strength of demand as the query commands score; .5206, determining whether the query command needs strength score is greater than a predetermined threshold; .5207, if larger than the set the predetermined threshold value, places the highest score query instructions strength of demand, as the demand for the type of query command intent requirement; .5208, if less than the set threshold value, it is determined that no significant demand for the query command intent.
15.根据权利要求10所述的搜索方法,其特征在于,所述表达模板库的构建方法,包括以下流程:·5300、抽取在用户历史行为库中包含知识片段的查询指令;·5301、将所述知识库片段替换成通用符号,生成候选表达模板;·5302、统计生成的所述候选表达模板符合的知识库片段的数量;·5303、判断所述数量是否大于设定阈值;·5304、若大于设定阈值,则将所述候选表达模板作为表达模板,并存于数据库中,生成表达模板库;·5305、若小于设定阈值,则舍弃所述候选表达模板。 15. The search method according to claim 10, wherein the expression construct method template library, including the following processes: · 5300, taking the query instruction contains pieces of knowledge in the history of the behavior of library users; * 5301, will The knowledge base fragments replace common symbols, generating a candidate expression template; • The number of 5302, the statistics generated by the candidate fragment expression template matching knowledge base; • 5303 to determine whether the number is greater than the set threshold; · 5304, If more than the set threshold, the candidate will be the expression of a template as an expression template and stored in the database, generating expression template library; * 5305, if less than the set threshold, then discarded the candidate expression template.
16. 一种搜索方法,其特征在于,所述搜索方法包括以下步骤:·51、接收查询指令;·52、基于知识库和表达模板库对所述查询指令进行需求意图分析,明确所述查询指令的需求意图,同时,基于所述知识库对接收到的查询指令进行语义扩充;·53、将带有需求意图并扩充语义的查询指令在数据库中搜索,得到搜索结果;·54、输出所述搜索结果。 16. A search method, wherein the search method comprising the steps of: 51, receiving a query command; * 52, based on knowledge and expression template library instruction requirement of the query intent analysis, clear the query Demand intent instruction, while the Knowledge-based query instructions received semantic expansion; * 53, the intention with the demand and the expansion of semantic search query instructions in the database, get the search results; * 54, outputs above the search results.
17.根据权利要求16所述的搜索方法,其特征在于,所述数据库为网页存储库或与所述需求意图相对应的垂直搜索数据库。 17. The search method according to claim 16, characterized in that the database is a repository or web page with the intention of demand corresponding vertical search database.
18.根据权利要求16所述的搜索方法,其特征在于,所述“基于知识库对所述查询指令进行需求意图分析,明确所述查询指令的需求意图”具体包括以下流程:·5200、通过用户历史行为库给知识库中的各个知识片段的各个需求意图打分,使各个知识片段都具有相应的需求意图得分;·5201、将所述查询指令与知识片段匹配,得到与所述查询指令相匹配的至少一个知识片段;·5202、将与所述查询指令相匹配的知识片段的需求意图得分加总,得到第一分数;·5203、通过与所述查询指令相匹配的知识片段在所述知识库中的从属关系,加减所述第一分数,得到知识库整体需求得分;·5204、判断所述知识库整体需求得分是否大于一设定阈值;·5205、若大于所述设定阈值,则以所述知识库整体需求得分最高的需求类型作为所述查询指令的需求意图;·5206、若小于所述设定阈值,则判断所述查询指令无明显需求意图。 18. The search method according to claim 16, characterized in that said "Knowledge-based query instructions on the intent requirement analysis needs clear intent of the query command," specifically includes the following processes: · 5200, by user behavior history database to individual requirements of each knowledge fragment Knowledge intent scoring, so that all pieces of knowledge has a corresponding demand intention score; * 5201, the query instruction and knowledge fragment match to give instructions with respect to the query Match at least one fragment knowledge; * 5202, with the intention to demand that match the query instructions knowledge fragments score summed to obtain a first score; * 5203, with the instruction that matches the query fragment in the knowledge affiliation Knowledge Base, plus or minus the first score, the overall demand score obtained knowledge; * 5204, overall demand for judging the knowledge base score is greater than a predetermined threshold; * 5205, if greater than the predetermined threshold , places the highest score overall demand for knowledge requirement type as the query command intent requirement; * 5206, if less than the set threshold value, it is determined that no significant demand for the query command intent.
19.根据权利要求16所述的搜索方法,其特征在于,所述“基于知识库对所述查询指令进行需求意图分析,明确所述查询指令的需求意图”具体包括以下流程:·5200、通过用户历史行为库给知识库中的各个知识片段的各个需求意图打分,使各个知识片段都具有相应的需求意图得分;·5201、将所述查询指令与知识片段和表达模板匹配,得到与所述查询指令相匹配的至少一个知识片段和一表达模板;·5202、将与所述查询指令相匹配的知识片段的需求意图得分加总,得到第一分数;·5203、通过与所述查询指令相匹配的知识片段在所述知识库中的从属关系,加减所述第一分数,得到知识库整体需求得分;·5204、对所述查询指令在表达模板层面上进行打分,得到表达模板得分;·5205、将知识库整体需求得分与表达模板得分的加权之和作为查询指令需求强度得分;·5206、判断所述查询指令需求强度得分是否大于一设定阈值;·5207、若大于所述设定阈值,则以查询指令需求强度得分最高的需求类型作为所述查询指令的需求意图;·5208、若小于所述设定阈值,则判断所述查询指令无明显需求意图。 19. The search method according to claim 16, characterized in that said "Knowledge-based query instructions on the intent requirement analysis needs clear intent of the query command," specifically includes the following processes: · 5200, by user behavior history database to individual requirements of each knowledge fragment Knowledge intent scoring, so that all pieces of knowledge has a corresponding demand intention score; * 5201, the query commands and pieces of knowledge and expression template matching, and get the query command match fragments and a knowledge of at least one expression templates; * 5202, with the intention to demand that match the query instructions knowledge fragments score summed to obtain a first score; * 5203, through to the query command phase matching pieces of knowledge affiliation in the Knowledge Base, plus or minus the first score, the score to give the overall demand for knowledge; * 5204, for instruction in the query expression of scoring on the template level, to give expression template score; · 5205, the overall demand for knowledge and expression templates score score weighted sum of the strength of demand as the query commands score; * 5206, determine whether the query command needs strength score is greater than a predetermined threshold; * 5207, if it exceeds the set the predetermined threshold value, places the highest score query instructions strength of demand, as the demand for the type of query command intent requirement; * 5208, if less than the set threshold value, it is determined that no significant demand for the query command intent.
20.根据权利要求16所述的搜索方法,其特征在于,所述表达模板库的构建方法,包括以下流程:5300、抽取在用户历史行为库中包含知识片段的查询指令;5301、将所述知识库片段替换成通用符号,生成候选表达模板;5302、统计生成的所述候选表达模板符合的知识库片段的数量;5303、判断所述数量是否大于设定阈值;5304、若大于设定阈值,则将所述候选表达模板作为表达模板,并存于数据库中,生成表达模板库;5305、若小于设定阈值,则舍弃所述候选表达模板。 20. The search method according to claim 16, wherein the expression construct method template library, including the following processes: 5300, taking historical behavior in the user query instructions contained in the library of knowledge fragments; 5301, the Knowledge fragment replaced by generic symbols, generating a candidate expression template; 5302, the number of statistics generated in line with the candidate's knowledge expression template fragments; 5303 determines whether the number is greater than the set threshold; 5304, if more than the set threshold value , then the candidate expression as an expression template Templates and stored in the database, generating expression template library; 5305, if less than the set threshold, then discarded the candidate expression template.
21. 一种搜索引擎,其特征在于,所述搜索引擎包括:UI模块,用于接收查询指令,且所述UI模块还用于接收搜索模块返回的搜索结果,并将所述搜索结果拼装为结果页面后输出;需求意图分析模块,用于基于知识库对所述查询指令进行需求意图分析,明确所述查询指令的需求意图;搜索模块,用于将带有需求意图的所述查询指令在数据库中搜索,得到搜索结果; 知识库,用于存储先验知识。 21. A search engine, wherein the search engine include: UI module for receiving a query command, and the UI module is further configured to receive the search module returns the search results, and assembly of the search results Results page output; demand intent analysis module for Knowledge-based query instructions on the intent requirement analysis, clear intent of the query command needs; search module for the query instructions with the intent requirement in a database search, the search results obtained; repository for storing a priori knowledge.
22.根据权利要求21所述的搜索引擎,其特征在于,所述搜索引擎还包括:web服务模块,用于通过网络协议接收客户端发出的查询指令,并将所述查询指令转到所述UI模块,且所述web服务模块还用于接收所述UI模块返回的结果页面,并将所述结果页面返回至所述客户端。 22. A search engine as claimed in claim 21, characterized in that said search engine further comprising: web service module for receiving a query instruction sent by the client through the network protocol, and the instruction to check the UI module and the web service module is further configured to receive the UI module returns results page and the results page returned to the client.
23.根据权利要求21所述的搜索引擎,其特征在于,所述搜索引擎还包括: 用户历史行为库,用于存储用户历史搜索记录。 23. A search engine as claimed in claim 21, characterized in that said search engine further comprises: a user behavior history database for storing user history search history.
24.根据权利要求23所述的搜索引擎,其特征在于,所述用户历史搜索记录包括:查询指令、查询次数,以及加权点击数。 24. A search engine as claimed in claim 23, characterized in that the user search history records include: query commands, queries, and the weighted number of clicks.
25.根据权利要求23或24所述的搜索引擎,其特征在于,所述搜索引擎还包括:表达模板挖掘模块,用于根据所述知识库中的知识片段和所述用户历史行为库中的用户历史查询指令,挖掘表达模板,并将所述表达模板存储于表达模板库; 表达模板库,用于存储由所述表达模板挖掘模块挖掘出的表达模板。 25. The search engine according to claim 23 or claim 24, wherein said search engine further comprises: Expression templates mining module for the knowledge base and the knowledge fragment library user behavior history Users historical inquiry instruction, mining expression template, and the expression templates are stored in the template library expression; expression template library for storing the expression template mining module excavated expression templates.
26.根据权利要求21所述的搜索引擎,其特征在于,所述搜索引擎还包括: 结构分类模块,用于基于所述知识库对所述查询指令进行语义扩充。 26. A search engine as claimed in claim 21, characterized in that said search engine further comprising: a structural classification module, based on the knowledge base for the semantic query expansion instruction.
27.根据权利要求21所述的搜索引擎,其特征在于,所述数据库为网页存储库或与所述需求意图相对应的垂直搜索数据库。 27. A search engine as claimed in claim 21, wherein said database is a repository or web page with the intention of demand corresponding vertical search database.
28.根据权利要求27所述的搜索引擎,其特征在于,所述网页存储库用于存储网页数据和该网页数据的索引信息;所述垂直搜索数据库用于存储特定类别数据和该特定类别数据的索引信息。 28. The search engine as claimed in claim 27, characterized in that said page index information repository for storing data pages and the page data; storing a particular category of data and the particular data category for the search database vertical The index information.
Beschreibung  übersetzt aus folgender Sprache: Chinesisch

搜索方法及搜索引擎 Search methods and search engine

技术领域 Technical Field

[0001] 本发明涉及搜索引擎技术,尤其涉及一种基于知识库对查询指令进行需求分析与解析的搜索方法及搜索引擎。 [0001] The present invention relates to search engine technology, particularly to a knowledge-based query instructions demand analysis and analytical search methods and search engine.

背景技术 Background

[0002] 随着互联网上信息的飞速增长,网络上充斥了越来越多的冗余信息,而对于在网络上搜寻自己所需要信息的互联网用户而言,面对这些漫无边际的信息无疑像大海捞针。 [0002] With the rapid growth of information on the Internet, the network filled with more and more redundant information, and for searching for information on the network of Internet users in terms of their own needs, to face these endless information will undoubtedly like the needle in a haystack . 搜索引擎的出现无疑在一定程度上为用户的搜索需求带来了很大便利。 Occurrences of the search engine is undoubtedly a certain extent for the user's search needs to bring a great convenience. 搜索引擎是一种在网络上应用的软件系统,其以一定的策略在网络上搜集和发现信息,并在对信息进行处理和组织后,为用户提供互联网上的信息搜索服务。 Search engine is a software application on a network system in order to collect a certain strategy and find information on the Web, and, after processing the information and organization, to provide users with information search services on the Internet. 通常,这种软件系统提供一个网页界面, 让用户在客户端通过浏览器软件提交搜索词,然后很快返回一个可能和用户输入的搜索内容相关的信息列表。 Often, this software provides a web interface, allowing users on the client browser software Submit search term, and then quickly return to the list of information and the user may enter a search related to the content. 这个列表通常会包括上万个条目,每个条目代表一篇搜索到的相关网页。 The list usually includes tens of thousands of entries, each entry represents a search for relevant pages.

[0003] 过去十几年以来,相应地,众多的互联网搜索引擎及对应的网站应运而生,这中间的佼佼者包括百度公司的百度搜索(WWW. baidu. com)和谷歌公司的谷歌搜索(www. google, cn)。 [0003] Since the last ten years, and accordingly, a large number of Internet search engines and the corresponding website came into being, the middle of the best companies including Baidu Baidu search (WWW. Baidu. Com) and Google's Google search ( www. google, cn).

[0004] 现有的搜索引擎对用户输入的查询指令大多是基于查询指令字符理解的,例如,用户输入查询指令为“Nokia手机”,基于现有的搜索引擎只能将该查询指令分词为“Nokia”和“手机”,且通过该分词结果在网页数据库索引中进行检索,将文本包括“Nokia” 和“手机”的网页Url输入,形成搜索结果,然而这种搜索引擎并不能对用户的查询指令进行内容与语义层次上的理解,例如,用户输入查询指令为“Nokia手机”,其并不能将这个查询指令理解为“Nokia”为“手机”中的一种品牌;当然,更不能理解查询指令的需求意图,以及查询指令的结构,不能对查询指令进行语义内容扩充等。 [0004] The existing search engine query commands entered by the user are mostly based on query command character to understand, for example, the user enters a query command is "Nokia mobile phone", only the query word instruction based on an existing search engine " Nokia "and" mobile phone ", and the results of that word on the page through the database index search, the text includes" Nokia "and" mobile phone "page Url input form search results, but this search engine does not query the user instructions to understand the content and the semantic level, for example, the user enters a query command is "Nokia mobile phone", it does not bring this query command understood as "Nokia" to "mobile phone" in a brand; of course, can not understand the query Demand intent instruction, as well as query command structure can not expand the semantic content of the query instruction and so on. 对于用户输入的表达形式多样化、需求意图多样化的查询指令,现有的基于字符的搜索引擎已经不能更好的满足用户的需求,造成用于查找不全,需要多次输入不同的查询指令才可能找到需要的搜索结果,搜索效率较低,浪费网络资源的问题。 For the expression of diverse forms of user input, demand diversification query instructions intentions existing character-based search engine has been unable to better meet the needs of users, resulting in failure to find, requiring multiple input before a different query instructions search result may find low search efficiency, waste of network resources.

发明内容 DISCLOSURE

[0005] 本发明的目的在于提供一种改进的搜索方法,其可在知识库的基础上,更好的理解用户输入的查询指令,分析查询指令的以图,解析查询指令的结构,对查询指令进行语义内容扩充。 [0005] The object of the present invention to provide an improved search method, which may be on the basis of the knowledge base, to better understand the user's query command input, analysis query command attempt to parse query command structure of the query instruction semantic content expansion.

[0006] 本发明的目的还在于提供一种实现上述搜索方法的改进的搜索引擎。 [0006] The object of the present invention is to provide a method to achieve improved search engine above search.

[0007] 为实现上述发明目的之一,本发明第一实施方式提供一种搜索方法,包括以下步骤: [0007] To achieve one object of the invention described above, a first embodiment of the present invention provides a searching method, comprising the steps of:

[0008] Si、接收查询指令; [0008] Si, receiving a query command;

[0009] S2、基于知识库对所述查询指令进行需求意图分析,明确所述查询指令的需求意图; [0009] S2, based on knowledge of the intention of the query instructions demand analysis, demand a clear intention of the query command;

[0010] S3、将带有需求意图的所述查询指令在数据库中搜索,得到搜索结果; [0010] S3, with the needs of the intended search query instructions in the database, get the search results;

[0011] S4、输出所述搜索结果。 [0011] S4, the output of the search results.

[0012] 作为本发明的进一步改进,所述数据库为网页存储库或与所述需求意图相对应的垂直搜索数据库。 [0012] As a further refinement of the invention, the database for the web repository or with the intent requirement corresponding vertical search databases.

[0013] 作为本发明的进一步改进,在所述S2步骤和S3步骤间,还包括语义扩充步骤: [0013] As a further improvement of the present invention, during the step S2 and the step S3, further comprising the steps of semantic Expansion:

[0014] 基于所述知识库对所述查询指令进行语义扩充。 [0014] Based on the knowledge of the semantic query expansion instruction.

[0015] 作为本发明的进一步改进,所述“基于知识库对所述查询指令进行需求意图分析, 明确所述查询指令的需求意图”具体包括以下流程: [0015] As a further refinement of the invention, the "Knowledge-based query instructions on the intent requirement analysis needs clear intent of the query command," specifically includes the following processes:

[0016] S200、通过用户历史行为库给知识库中的各个知识片段的各个需求意图打分,使各个知识片段都具有相应的需求意图得分; [0016] S200, user behavior history database repository to the various needs of the various pieces of knowledge of the intention of scoring, so that all pieces of knowledge has a corresponding demand intention score;

[0017] S201、将所述查询指令与知识片段匹配,得到与所述查询指令相匹配的至少一个知识片段; [0017] S201, the query instruction and match pieces of knowledge to give instructions to the query matches the knowledge of at least one segment;

[0018] S202、将与所述查询指令相匹配的知识片段的需求意图得分加总,得到第一分数; [0018] S202, the intent of the query command needs to match the pieces of knowledge scores are summed to obtain a first fraction;

[0019] S203、通过与所述查询指令相匹配的知识片段在所述知识库中的从属关系,加减所述第一分数,得到知识库整体需求得分; [0019] S203, with the instruction that matches the query fragment affiliation knowledge in the knowledge base, subtract the first score, get knowledge score overall demand;

[0020] S204、判断所述知识库整体需求得分是否大于一设定阈值; [0020] S204, determines the overall demand knowledge score is greater than a predetermined threshold;

[0021] S205、若大于所述设定阈值,则以所述知识库整体需求得分最高的需求类型作为所述查询指令的需求意图; [0021] S205, if it exceeds the set threshold value, places the highest score overall demand for knowledge requirement type as the query command intent requirement;

[0022] S206、若小于所述设定阈值,则判断所述查询指令无明显需求意图。 [0022] S206, if less than the set threshold value, it is determined that no significant demand for the query command intent.

[0023] 作为本发明的进一步改进,所述“基于知识库对所述查询指令进行需求意图分析, 明确所述查询指令的需求意图”具体包括以下流程: [0023] As a further refinement of the invention, the "Knowledge-based query instructions on the intent requirement analysis needs clear intent of the query command," specifically includes the following processes:

[0024] S200、通过用户历史行为库给知识库中的各个知识片段的各个需求意图打分,使各个知识片段都具有相应的需求意图得分; [0024] S200, user behavior history database repository to the various needs of the various pieces of knowledge of the intention of scoring, so that all pieces of knowledge has a corresponding demand intention score;

[0025] S201、将所述查询指令与知识片段和表达模板匹配,得到与所述查询指令相匹配的至少一个知识片段和一表达模板; [0025] S201, the query commands and pieces of knowledge and expression template matching, to give instruction to the query matches the knowledge of at least one segment and a template expression;

[0026] S202、将与所述查询指令相匹配的知识片段的需求意图得分加总,得到第一分数; [0026] S202, the intent of the query command needs to match the pieces of knowledge scores are summed to obtain a first fraction;

[0027] S203、通过与所述查询指令相匹配的知识片段在所述知识库中的从属关系,加减所述第一分数,得到知识库整体需求得分; [0027] S203, with the instruction that matches the query fragment affiliation knowledge in the knowledge base, subtract the first score, get knowledge score overall demand;

[0028] S204、对所述查询指令在表达模板层面上进行打分,得到表达模板得分; [0028] S204, the query command for scoring template in expression level was expressed template score;

[0029] S205、将知识库整体需求得分与表达模板得分的加权之和作为查询指令需求强度得分; [0029] S205, the overall demand for knowledge and expression templates score score weighted sum of scores as the query command needs strength;

[0030] S206、判断所述查询指令需求强度得分是否大于一设定阈值; [0030] S206, determine whether the query command needs strength score is greater than a predetermined threshold;

[0031] S207、若大于所述设定阈值,则以查询指令需求强度得分最高的需求类型作为所述查询指令的需求意图; [0031] S207, if greater than the predetermined threshold, the query command places the highest score of the strength of demand, as the demand for the type of query command intent requirement;

[0032] S208、若小于所述设定阈值,则判断所述查询指令无明显需求意图。 [0032] S208, if less than the set threshold value, it is determined that no significant demand for the query command intent.

[0033] 为实现上述发明目的之一,本发明第二实施方式提供一种搜索方法,包括以下步骤: [0033] To achieve one object of the invention described above, the second embodiment of the present invention provides a searching method, comprising the steps of:

[0034] Si、接收查询指令; [0034] Si, receiving a query command;

[0035] S2、基于知识库对所述查询指令进行需求意图分析,明确所述查询指令的需求意图,同时,基于所述知识库对所述查询指令进行语义扩充; [0035] S2, based on knowledge of the intention of the query instructions demand analysis, demand a clear intention of the query command, while based on the knowledge base for the expansion of semantic query instructions;

[0036] S3、将带有需求意图并扩充语义的查询指令在数据库中搜索,得到搜索结果; [0036] S3, the intention with the demand and the expansion of semantic search query instructions in the database, get the search results;

[0037] S4、输出所述搜索结果。 [0037] S4, the output of the search results.

[0038] 作为本发明的进一步改进,所述数据库为网页存储库或与所述需求意图相对应的垂直搜索数据库。 [0038] As a further refinement of the invention, the database for the web repository or with the intent requirement corresponding vertical search databases.

[0039] 作为本发明的进一步改进,所述“基于知识库对所述查询指令进行需求意图分析, 明确所述查询指令的需求意图”具体包括以下流程: [0039] As a further refinement of the invention, the "Knowledge-based query instructions on the intent requirement analysis needs clear intent of the query command," specifically includes the following processes:

[0040] S200、通过用户历史行为库给知识库中的各个知识片段的各个需求意图打分,使各个知识片段都具有相应的需求意图得分; [0040] S200, user behavior history database repository to the various needs of the various pieces of knowledge of the intention of scoring, so that all pieces of knowledge has a corresponding demand intention score;

[0041] S201、将所述查询指令与知识片段匹配,得到与所述查询指令相匹配的至少一个知识片段; [0041] S201, the query instruction and match pieces of knowledge to give instructions to the query matches the knowledge of at least one segment;

[0042] S202、将与所述查询指令相匹配的知识片段的需求意图得分加总,得到第一分数; [0042] S202, the intent of the query command needs to match the pieces of knowledge scores are summed to obtain a first fraction;

[0043] S203、通过与所述查询指令相匹配的知识片段在所述知识库中的从属关系,加减所述第一分数,得到知识库整体需求得分; [0043] S203, with the instruction that matches the query fragment affiliation knowledge in the knowledge base, subtract the first score, get knowledge score overall demand;

[0044] S204、判断所述知识库整体需求得分是否大于一设定阈值; [0044] S204, to judge the overall demand for the knowledge base score is greater than a predetermined threshold;

[0045] S205、若大于所述设定阈值,则以所述知识库整体需求得分最高的需求类型作为所述查询指令的需求意图; [0045] S205, if it exceeds the set threshold value, places the highest score overall demand for knowledge requirement type as the query command intent requirement;

[0046] S206、若小于所述设定阈值,则判断所述查询指令无明显需求意图。 [0046] S206, if less than the set threshold value, it is determined that no significant demand for the query command intent.

[0047] 作为本发明的进一步改进,所述“基于知识库对所述查询指令进行需求意图分析, 明确所述查询指令的需求意图”具体包括以下流程: [0047] As a further refinement of the invention, the "Knowledge-based query instructions on the intent requirement analysis needs clear intent of the query command," specifically includes the following processes:

[0048] S200、通过用户历史行为库给知识库中的各个知识片段的各个需求意图打分,使各个知识片段都具有相应的需求意图得分; [0048] S200, user behavior history database repository to the various needs of the various pieces of knowledge of the intention of scoring, so that all pieces of knowledge has a corresponding demand intention score;

[0049] S201、将所述查询指令与知识片段和表达模板匹配,得到与所述查询指令相匹配的至少一个知识片段和一表达模板; [0049] S201, the query commands and pieces of knowledge and expression template matching, to give instruction to the query matches the knowledge of at least one segment and a template expression;

[0050] S202、将与所述查询指令相匹配的知识片段的需求意图得分加总,得到第一分数; [0050] S202, the intent of the query command needs to match the pieces of knowledge scores are summed to obtain a first fraction;

[0051] S203、通过与所述查询指令相匹配的知识片段在所述知识库中的从属关系,加减所述第一分数,得到知识库整体需求得分; [0051] S203, with the instruction that matches the query fragment affiliation knowledge in the knowledge base, subtract the first score, get knowledge score overall demand;

[0052] S204、对所述查询指令在表达模板层面上进行打分,得到表达模板得分; [0052] S204, the query command for scoring template in expression level was expressed template score;

[0053] S205、将知识库整体需求得分与表达模板得分的加权之和作为查询指令需求强度得分; [0053] S205, the overall demand for knowledge and expression templates score score weighted sum of scores as the query command needs strength;

[0054] S206、判断所述查询指令需求强度得分是否大于一设定阈值; [0054] S206, determine whether the query command needs strength score is greater than a predetermined threshold;

[0055] S207、若大于所述设定阈值,则以查询指令需求强度得分最高的需求类型作为所述查询指令的需求意图; [0055] S207, if greater than the predetermined threshold, the query command places the highest score of the strength of demand, as the demand for the type of query command intent requirement;

[0056] S208、若小于所述设定阈值,则判断所述查询指令无明显需求意图。 [0056] S208, if less than the set threshold value, it is determined that no significant demand for the query command intent. [0057] 为实现上述发明目的之一,本发明第三实施方式提供一种搜索方法,包括以下步骤: [0057] To achieve one object of the invention described above, the third embodiment of the present invention provides a searching method, comprising the steps of:

[0058] Si、接收查询指令; [0058] Si, receiving a query command;

[0059] S2、基于知识库和表达模板库对所述查询指令进行需求意图分析,明确所述查询指令的需求意图; [0059] S2, based on knowledge and expression template library for the query instructions intention demand analysis, demand a clear intention of the query command;

[0060] S3、将带有需求意图的所述查询指令在数据库中搜索,得到搜索结果; [0060] S3, with the needs of the intended search query instructions in the database, get the search results;

[0061] S4、输出所述搜索结果。 [0061] S4, the output of the search results.

[0062] 作为本发明的进一步改进,所述数据库为网页存储库或与所述需求意图相对应的垂直搜索数据库。 [0062] As a further refinement of the invention, the database for the web repository or with the intent requirement corresponding vertical search databases.

[0063] 作为本发明的进一步改进,在所述S2步骤和S3步骤间,还包括语义扩充步骤: [0063] As a further improvement of the invention, the step between the S2 and S3 step, further comprising the step of semantic expansion:

[0064] 基于所述知识库对所述查询指令进行语义扩充。 [0064] Based on the knowledge of the semantic query expansion instruction.

[0065] 作为本发明的进一步改进,所述“基于知识库对所述查询指令进行需求意图分析, 明确所述查询指令的需求意图”具体包括以下流程: [0065] As a further refinement of the invention, the "Knowledge-based query instructions on the intent requirement analysis needs clear intent of the query command," specifically includes the following processes:

[0066] S200、通过用户历史行为库给知识库中的各个知识片段的各个需求意图打分,使各个知识片段都具有相应的需求意图得分; [0066] S200, user behavior history database repository to the various needs of the various pieces of knowledge of the intention of scoring, so that all pieces of knowledge has a corresponding demand intention score;

[0067] S201、将所述查询指令与知识片段匹配,得到与所述查询指令相匹配的至少一个知识片段; [0067] S201, the query instruction and match pieces of knowledge to give instructions to the query matches the knowledge of at least one segment;

[0068] S202、将与所述查询指令相匹配的知识片段的需求意图得分加总,得到第一分数; [0068] S202, the intent of the query command needs to match the pieces of knowledge scores are summed to obtain a first fraction;

[0069] S203、通过与所述查询指令相匹配的知识片段在所述知识库中的从属关系,加减所述第一分数,得到知识库整体需求得分; [0069] S203, with the instruction that matches the query fragment affiliation knowledge in the knowledge base, subtract the first score, get knowledge score overall demand;

[0070] S204、判断所述知识库整体需求得分是否大于一设定阈值; [0070] S204, determines the overall demand knowledge score is greater than a predetermined threshold;

[0071] S205、若大于所述设定阈值,则以所述知识库整体需求得分最高的需求类型作为所述查询指令的需求意图; [0071] S205, if it exceeds the set threshold value, places the highest score overall demand for knowledge requirement type as the query command intent requirement;

[0072] S206、若小于所述设定阈值,则判断所述查询指令无明显需求意图。 [0072] S206, if less than the set threshold value, it is determined that no significant demand for the query command intent.

[0073] 作为本发明的进一步改进,所述“基于知识库对所述查询指令进行需求意图分析, 明确所述查询指令的需求意图”具体包括以下流程: [0073] As a further refinement of the invention, the "Knowledge-based query instructions on the intent requirement analysis needs clear intent of the query command," specifically includes the following processes:

[0074] S200、通过用户历史行为库给知识库中的各个知识片段的各个需求意图打分,使各个知识片段都具有相应的需求意图得分; [0074] S200, user behavior history database repository to the various needs of the various pieces of knowledge of the intention of scoring, so that all pieces of knowledge has a corresponding demand intention score;

[0075] S201、将所述查询指令与知识片段和表达模板匹配,得到与所述查询指令相匹配的至少一个知识片段和一表达模板; [0075] S201, the query commands and pieces of knowledge and expression template matching, to give instruction to the query matches the knowledge of at least one segment and a template expression;

[0076] S202、将与所述查询指令相匹配的知识片段的需求意图得分加总,得到第一分数; [0076] S202, the intent of the query command needs to match the pieces of knowledge scores are summed to obtain a first fraction;

[0077] S203、通过与所述查询指令相匹配的知识片段在所述知识库中的从属关系,加减所述第一分数,得到知识库整体需求得分; [0077] S203, with the instruction that matches the query fragment affiliation knowledge in the knowledge base, subtract the first score, get knowledge score overall demand;

[0078] S204、对所述查询指令在表达模板层面上进行打分,得到表达模板得分; [0078] S204, the query command for scoring template in expression level was expressed template score;

[0079] S205、将知识库整体需求得分与表达模板得分的加权之和作为查询指令需求强度得分; [0079] S205, the overall demand for knowledge and expression templates score score weighted sum of scores as the query command needs strength;

[0080] S206、判断所述查询指令需求强度得分是否大于一设定阈值; [0080] S206, determine whether the query command needs strength score is greater than a predetermined threshold;

11[0081] S207、若大于所述设定阈值,则以查询指令需求强度得分最高的需求类型作为所述查询指令的需求意图; 11 [0081] S207, if greater than the predetermined threshold, the query command places the highest score of the strength of demand, as the demand for the type of query command intent requirement;

[0082] S208、若小于所述设定阈值,则判断所述查询指令无明显需求意图。 [0082] S208, if less than the set threshold value, it is determined that no significant demand for the query command intent.

[0083] 作为本发明的进一步改进,所述表达模板库的构建方法,包括以下流程: [0083] As a further refinement of the invention, the expression construct method template library, including the following processes:

[0084] S300、抽取在用户历史行为库中包含知识片段的查询指令; [0084] S300, extracting query instructions contain pieces of knowledge in the history of the behavior of library users;

[0085] S301、将所述知识库片段替换成通用符号,生成候选表达模板; [0085] S301, the knowledge base fragments replace common symbols, generating a candidate expression template;

[0086] S302、统计生成的所述候选表达模板符合的知识库片段的数量; [0086] S302, the number of statistics generated in line with the candidate's knowledge expression template fragments;

[0087] S303、判断所述数量是否大于设定阈值; [0087] S303, determines whether the number is greater than the predetermined threshold;

[0088] S304、若大于设定阈值,则将所述候选表达模板作为表达模板,并存于数据库中, 生成表达模板库; [0088] S304, if more than the set threshold, the candidate expression as an expression template Templates and stored in the database, generating expression template library;

[0089] S305、若小于设定阈值,则舍弃所述候选表达模板。 [0089] S305, if less than the set threshold, then discarded the candidate expression template.

[0090] 为实现上述发明目的之一,本发明第四实施方式提供一种搜索方法,包括以下步骤: [0090] To achieve one object of the invention described above, the fourth embodiment of the present invention provides a searching method, comprising the steps of:

[0091] Si、接收查询指令; [0091] Si, receiving a query command;

[0092] S2、基于知识库和表达模板库对所述查询指令进行需求意图分析,明确所述查询指令的需求意图,同时,基于所述知识库对接收到的查询指令进行语义扩充; [0092] S2, based on knowledge and expression template library for the query instructions intention demand analysis, demand a clear intention of the query command, while the Knowledge-based query instructions received semantic expansion;

[0093] S3、将带有需求意图并扩充语义的查询指令在数据库中搜索,得到搜索结果; [0093] S3, the intention with the demand and the expansion of semantic search query instructions in the database, get the search results;

[0094] S4、输出所述搜索结果。 [0094] S4, the output of the search results.

[0095] 作为本发明的进一步改进,所述数据库为网页存储库或与所述需求意图相对应的垂直搜索数据库。 [0095] As a further refinement of the invention, the database for the web repository or with the intent requirement corresponding vertical search databases.

[0096] 作为本发明的进一步改进,所述“基于知识库对所述查询指令进行需求意图分析, 明确所述查询指令的需求意图”具体包括以下流程: [0096] As a further refinement of the invention, the "Knowledge-based query instructions on the intent requirement analysis needs clear intent of the query command," specifically includes the following processes:

[0097] S200、通过用户历史行为库给知识库中的各个知识片段的各个需求意图打分,使各个知识片段都具有相应的需求意图得分; [0097] S200, user behavior history database repository to the various needs of the various pieces of knowledge of the intention of scoring, so that all pieces of knowledge has a corresponding demand intention score;

[0098] S201、将所述查询指令与知识片段匹配,得到与所述查询指令相匹配的至少一个知识片段; [0098] S201, the query instruction and match pieces of knowledge to give instructions to the query matches the knowledge of at least one segment;

[0099] S202、将与所述查询指令相匹配的知识片段的需求意图得分加总,得到第一分数; [0099] S202, the intent of the query command needs to match the pieces of knowledge scores are summed to obtain a first fraction;

[0100] S203、通过与所述查询指令相匹配的知识片段在所述知识库中的从属关系,加减所述第一分数,得到知识库整体需求得分; [0100] S203, with the instruction that matches the query fragment affiliation knowledge in the knowledge base, subtract the first score, get knowledge score overall demand;

[0101] S204、判断所述知识库整体需求得分是否大于一设定阈值; [0101] S204, determines the overall demand knowledge score is greater than a predetermined threshold;

[0102] S205、若大于所述设定阈值,则以所述知识库整体需求得分最高的需求类型作为所述查询指令的需求意图; [0102] S205, if it exceeds the set threshold value, places the highest score overall demand for knowledge requirement type as the query command intent requirement;

[0103] S206、若小于所述设定阈值,则判断所述查询指令无明显需求意图。 [0103] S206, if less than the set threshold value, it is determined that no significant demand for the query command intent.

[0104] 作为本发明的进一步改进,所述“基于知识库对所述查询指令进行需求意图分析, 明确所述查询指令的需求意图”具体包括以下流程: [0104] As a further refinement of the invention, the "Knowledge-based query instructions on the intent requirement analysis needs clear intent of the query command," specifically includes the following processes:

[0105] S200、通过用户历史行为库给知识库中的各个知识片段的各个需求意图打分,使各个知识片段都具有相应的需求意图得分; [0105] S200, user behavior history database repository to the various needs of the various pieces of knowledge of the intention of scoring, so that all pieces of knowledge has a corresponding demand intention score;

[0106] S201、将所述查询指令与知识片段和表达模板匹配,得到与所述查询指令相匹配的至少一个知识片段和一表达模板; [0106] S201, the query commands and pieces of knowledge and expression template matching, to give instruction to the query matches the knowledge of at least one segment and a template expression;

[0107] S202、将与所述查询指令相匹配的知识片段的需求意图得分加总,得到第一分数; [0107] S202, the intent of the query command needs to match the pieces of knowledge scores are summed to obtain a first fraction;

[0108] S203、通过与所述查询指令相匹配的知识片段在所述知识库中的从属关系,加减所述第一分数,得到知识库整体需求得分; [0108] S203, with the instruction that matches the query fragment affiliation knowledge in the knowledge base, subtract the first score, get knowledge score overall demand;

[0109] S204、对所述查询指令在表达模板层面上进行打分,得到表达模板得分; [0109] S204, the query command for scoring template in expression level was expressed template score;

[0110] S205、将知识库整体需求得分与表达模板得分的加权之和作为查询指令需求强度得分; [0110] S205, the overall demand for knowledge and expression templates score score weighted sum of scores as the query command needs strength;

[0111] S206、判断所述查询指令需求强度得分是否大于一设定阈值; [0111] S206, determine whether the query command needs strength score is greater than a predetermined threshold;

[0112] S207、若大于所述设定阈值,则以查询指令需求强度得分最高的需求类型作为所述查询指令的需求意图; [0112] S207, if greater than the predetermined threshold, the query command places the highest score of the strength of demand, as the demand for the type of query command intent requirement;

[0113] S208、若小于所述设定阈值,则判断所述查询指令无明显需求意图。 [0113] S208, if less than the set threshold value, it is determined that no significant demand for the query command intent.

[0114] 作为本发明的进一步改进,所述表达模板库的构建方法,包括以下流程: [0114] As a further refinement of the invention, the expression construct method template library, including the following processes:

[0115] S300、抽取在用户历史行为库中包含知识片段的查询指令; [0115] S300, extracting query instructions contain pieces of knowledge in the history of the behavior of library users;

[0116] S301、将所述知识库片段替换成通用符号,生成候选表达模板; [0116] S301, the knowledge base fragments replace common symbols, generating a candidate expression template;

[0117] S302、统计生成的所述候选表达模板符合的知识库片段的数量; [0117] S302, the number of statistics generated in line with the candidate's knowledge expression template fragments;

[0118] S303、判断所述数量是否大于设定阈值; [0118] S303, determines whether the number is greater than the predetermined threshold;

[0119] S304、若大于设定阈值,则将所述候选表达模板作为表达模板,并存于数据库中, 生成表达模板库; [0119] S304, if more than the set threshold, the candidate expression as an expression template Templates and stored in the database, generating expression template library;

[0120] S305、若小于设定阈值,则舍弃所述候选表达模板。 [0120] S305, if less than the set threshold, then discarded the candidate expression template.

[0121] 相应地,作为实现上述发明另一目的,本发明一实施方式提供一种搜索引擎,包括: [0121] Accordingly, as the implementation is another object of the invention described above, an embodiment of the present invention to provide a search engine, including:

[0122] UI模块,用于接收查询指令,且所述UI模块还用于接收搜索模块返回的搜索结果,并将所述搜索结果拼装为结果页面后输出; [0122] UI module for receiving a query command, and the UI module is further configured to receive the search module returns the search results, and assembled as a result of the search results page after output;

[0123] 需求意图分析模块,用于基于知识库对所述查询指令进行需求意图分析,明确所述查询指令的需求意图; [0123] intent requirement analysis module for knowledge based on the intention to analyze the needs of the query instructions, clear intent of the query needs instruction;

[0124] 搜索模块,用于将带有需求意图的所述查询指令在数据库中搜索,得到搜索结果; [0124] The search module, with demand for the intent of the query command searches the database to obtain search results;

[0125] 知识库,用于存储先验知识。 [0125] repository for storing a priori knowledge.

[0126] 作为本发明的进一步改进,所述搜索引擎还包括: [0126] As a further improvement of the invention, the search engine further comprises:

[0127] web服务模块,用于通过网络协议接收客户端发出的查询指令,并将所述查询指令转到所述UI模块,且所述web服务模块还用于接收所述UI模块返回的结果页面,并将所述结果页面返回至所述客户端。 [0127] web service module for receiving a query command sent by the client through the network protocol and the query instruction to the UI module and the web service module is further configured to receive the results of the UI module returns page and the results page returned to the client.

[0128] 作为本发明的进一步改进,所述搜索引擎还包括: [0128] As a further improvement of the invention, the search engine further comprises:

[0129] 用户历史行为库,用于存储用户历史搜索记录。 [0129] user behavior history database for storing user history search history.

[0130] 作为本发明的进一步改进,所述用户历史搜索记录包括:查询指令、查询次数,以及加权点击数。 [0130] As a further refinement of the invention, the user search history records include: query commands, queries, and the weighted number of clicks.

[0131] 作为本发明的进一步改进,所述搜索引擎还包括: [0131] As a further improvement of the invention, the search engine further comprises:

[0132] 表达模板挖掘模块,用于根据所述知识库中的知识片段和所述用户历史行为库中的用户历史查询指令,挖掘表达模板,并将所述表达模板存储于表达模板库; [0132] The expression template mining module, for historical inquiry instruction according to the knowledge in the knowledge fragments and historical behavior of the user library users, digging expression templates and template stored in the expression expression template library;

[0133] 表达模板库,用于存储由所述表达模板挖掘模块挖掘出的表达模板。 [0133] The expression template library for storing the expression template mining module excavated expression templates.

[0134] 作为本发明的进一步改进,所述搜索引擎还包括: [0134] As a further improvement of the invention, the search engine further comprises:

[0135] 结构分类模块,用于基于所述知识库对所述查询指令进行语义扩充。 [0135] structural classification module, based on the knowledge base for the query semantic expansion instruction.

[0136] 作为本发明的进一步改进,所述数据库为网页存储库或与所述需求意图相对应的垂直搜索数据库。 [0136] As a further refinement of the invention, the database for the web repository or with the intent requirement corresponding vertical search databases.

[0137] 作为本发明的进一步改进,所述网页存储库用于存储网页数据和该网页数据的索引信息; [0137] As a further refinement of the invention, the web repository for data and index information stored pages of the web page data;

[0138] 所述垂直搜索数据库用于存储特定类别数据和该特定类别数据的索引信息。 [0138] The vertical search databases for storing data and specific categories of data that particular category of index information.

[0139] 与现有技术相比,本发明的有益效果是:在知识库的基础上,更好的理解用户输入的查询指令,分析查询指令的以图,解析查询指令的结构,对查询指令进行语义内容扩充, 从而更好的指导搜索引擎选择优质的资源满足用户的搜索需求,使得用户搜索效率提高, 节约网络流量。 [0139] Compared with the prior art, the beneficial effects of the present invention are: on the basis of knowledge, a better understanding of query commands entered by the user, attempt to analyze query command parsing structure query command, query commands semantic content expansion, in order to better guide the search engine to select high-quality resources to meet users' search needs, enabling users to search for efficiency, saving network traffic.

附图说明 Brief Description

[0140] 图1是本发明搜索引擎与客户端实现互动的工作原理图; [0140] FIG. 1 is a search engine of the present invention to interact with the client's operating principle;

[0141] 图2是本发明搜索引擎第一实施方式的模块图; [0141] FIG. 2 is a search engine of the present invention is a block diagram of a first embodiment;

[0142] 图3是本发明搜索引擎第二实施方式的模块图; [0142] FIG. 3 is a search engine of the present invention is a block diagram of a second embodiment;

[0143] 图4是本发明搜索引擎第三实施方式的模块图; [0143] FIG. 4 is a search engine of the present invention is a block diagram of a third embodiment;

[0144] 图5是本发明搜索引擎第四实施方式的模块图; [0144] FIG. 5 is a search engine of the present invention is a block diagram of a fourth embodiment;

[0145] 图6是本发明知识库架构的示意图; [0145] FIG. 6 is a schematic diagram of the present invention repository architecture;

[0146] 图7是本发明搜索方法第一实施方式的流程图; [0146] FIG. 7 is a flowchart of search method of the first embodiment of the present invention;

[0147] 图8是本发明搜索方法第二实施方式的流程图; [0147] FIG. 8 is a flowchart of search method of the second embodiment of the present invention;

[0148] 图9是本发明搜索方法第三实施方式的流程图; [0148] FIG. 9 is a flowchart of search method of the third embodiment of the present invention;

[0149] 图10是本发明搜索方法第四实施方式的流程图; [0149] FIG. 10 is a flowchart of search method of the fourth embodiment of the present invention;

[0150] 图11是本发明“基于知识库对所述查询指令进行需求意图分析,明确所述查询指令的需求意图”步骤一实施方式的流程图; [0150] FIG. 11 is the present invention is "based on knowledge of the intention of the query instructions demand analysis, demand a clear intention of the query command" Step one embodiment of a flow chart;

[0151] 图12是本发明“基于知识库对所述查询指令进行需求意图分析,明确所述查询指令的需求意图”步骤另一实施方式的流程图; [0151] FIG. 12 is the present invention, "Knowledge is based on the intention of the query instructions demand analysis, demand a clear intention of the query command" step flow chart of another embodiment;

[0152] 图13是本发明表达模板库的构建方法的流程图; [0152] FIG. 13 is a flowchart template library construction method of the present invention expression;

[0153] 图14是本发明在线界面一实施方式的示意图; [0153] FIG. 14 is a schematic diagram of the present invention, an online interface to an embodiment;

[0154] 图15是“当用户点击垂直搜索结果跳转至新页面”中的新页面示意图。 [0154] FIG. 15 is a "vertical search results when a user clicks to jump to a new page," a new page in the schematic.

具体实施方式 DETAILED DESCRIPTION

[0155] 以下将结合附图所示的各实施方式对本发明进行详细描述。 [0155] The following drawings in conjunction with the embodiments of the present invention will be illustrated in detail below. 但这些实施方式并不限制本发明,本领域的普通技术人员根据这些实施方式所轻易做出的结构、方法、或功能上的变换均包含在本发明的保护范围内。 However, these embodiments do not limit the present invention, one of ordinary skill in the art structure made according to these embodiments easily, method, or conversion functions are included within the scope of the present invention.

[0156] 图1所示的本发明的搜索引擎10与客户端20实现互动的工作原理图。 [0156] FIG. 1 search engine 10 of the present invention shown to interact with the client 20 operating schematic. 本实施方式中,该客户端20包括一浏览器201,客户可通过该浏览器201打开搜索引擎在线展示的网页,并在网页中的对话框内输入查询指令,一般的,该输入的查询指令为文本信息,当然, 该查询指令还可以为图片信息、视频信息等等。 In this embodiment, the client 20 includes a browser 201, customers can open the search engine 201 online presence through the web browser, and enter the query command in the pages of the dialog box, in general, the input query instructions text message, of course, the query command can also image information, video information and so on. 所述搜索引擎10通过网络接收客户输入至所述浏览器中的查询指令,并对该查询指令进行搜索后,将搜索结果通过搜索引擎在线展示网页返回至该浏览器201。 The search engine 10 input via the network to the client browser receives the query commands and instructions to the query search, the search results page online presence through search engine to return to the browser 201. 其中,该搜索引擎10可以包括一台或多台服务器,该客户端20可以包括一个或多个用户终端设备,如个人计算机、笔记本电脑、无线电话、个人数字处理(PDA)、或其它计算机系统和通信系统。 Among them, the search engine 10 may include one or more servers, the client 20 may include one or more user devices such as personal computers, notebook computers, wireless telephones, personal digital processing (PDA), or other computer systems and communication systems.

[0157] 这些服务器和终端设备在架构上都包含一些基本组件,如总线、处理系统、存储系统、一个或多个输入/输出系统、和通信接口等。 [0157] The server and the terminal equipment in the structure contains a number of basic components, such as bus, handling systems, storage systems, one or more input / output systems, and communication interfaces. 总线可以包括一个或多个导线,用来实现服务器或终端设备各组件之间的通信。 Bus may include one or more wires, used to implement communication server or terminal device between components. 处理系统包括各类型的用来执行指令、处理进程或线程的处理器或微处理器。 Processing system includes various types of instructions for executing the processing process or thread processor or microprocessor. 存储系统可以包括存储动态信息的随机访问存储器(RAM)等动态存储器,和存储静态信息的只读存储器(ROM)等静态存储器,以及包括磁或光学记录介质与相应驱动的大容量存储器。 The storage system may include a dynamic random access memory for storing information (RAM) and other dynamic memory, and a read only memory for storing static information (ROM) and other static memory, and comprises a magnetic or optical recording medium and the corresponding drive mass storage. 输入系统供用户输入信息到服务器或终端设备,如键盘、鼠标、手写笔、声音识别系统、或生物测定系统等。 Enter system for the user to input information to the server or terminal device, such as a keyboard, mouse, pen, voice recognition systems, or biometric systems. 输出系统包括用来输出信息的显示器、打印机、扬声器等。 Output system for outputting information includes a display, a printer, a speaker, and the like. 通信接口用来使服务器或终端设备与其它系统或系统进行通信。 The communication interface is used to enable the server or terminal equipment with other systems or systems to communicate. 通信接口之间可通过有线连接、无线连接、或光连接连接到网络中,使搜索引擎10、客户端20间能够通过网络实现相互间的通信。 Between the communication interface can be connected via a wired connection, wireless, or optical connection to the network, so that the search engine 10, the client 20 can communicate with each other over the network. 网络可以包括局域网(LAN)、广域网(WAN)、电话网络如公共交换电话网(PSTN)、企业内部的互联网、因特网、或上述这些网络的结合等。 Network may comprise a local area network (LAN), a wide area network (WAN), a telephone network such as the Public Switched Telephone Network (PSTN), Internet internal, the Internet, or a combination of these and other networks.

[0158] 服务器和终端设备上均包含有用来管理系统资源、控制其它程序运行的操作系统软件,以及用来实现特定功能模块的应用软件。 [0158] on the server and the terminal equipment are used to manage system resources contain, control other programs running operating system software, and application software used to implement a specific function modules. 如图2所示,在本发明第一实施方式中,所述搜索引擎包括了web服务模块101、与web服务模块101交互通信的UI模块102、与所述UI模块102通信的需求意图分析模块103、与所述需求意图分析模块103通信的结构分析模块104、与所述结构分析模块104通信的搜索模块105,以及与所述需求意图分析模块103、所述结构分析模块104交互通信的知识库106、与所述知识库106通信的用户历史行为库107、与所述知识库106、用户历史行为库107通信的表达模板挖掘模块108、与所述表达模板挖掘模块108和所述需求意图分析模块103通信的表达模板库109,以及与所述搜索模块105通信的网页存储库110。 Figure 2, in a first embodiment of the present invention, the search engine shown comprises a web service module 101, and the UI module 101 interacts web service communication module 102, the UI module 102 and the communication needs analysis module intent 103, with the intent requirement analysis 103 communication module structure analysis module 104, and the structural analysis module 104 searches the communication module 105, and with the intent requirement analysis module 103, the knowledge of the structural analysis of interactive communication module 104 106 libraries, historical behavior of the knowledge base and user communication library 106 107, and the knowledge base 106, the expression template library historical behavior mining module user communication 108 107, and the expression template mining module 108 and the needs of intent Expression repository 110 web template library 109 communicating analysis module 103, and 105 in communication with the search module. 值得一提的是,这些模块即可存储并运行于同一服务器中, 也可存储并运行在多台服务器中。 It is worth mentioning that these modules can be stored and run on the same server, it can also be stored and run on multiple servers.

[0159] 所述web服务模块101用于通过网络协议接收从客户端20传来的查询指令,并将该查询指令转到UI模块102,另外,该web服务模块101还用于接收所述UI模块102返回的结果页面,并将所述结果页面返回至客户端20。 [0159] The web service module 101 for receiving a query command 20 coming from the client through the network protocol, and the query instruction to the UI module 102, In addition, the web service module 101 is further configured to receive the UI module 102 returns the result page and the results page returned to the client 20.

[0160] 所述UI模块102用于接收所述web服务模块101传送的查询指令,并将该查询指令发送至所述查询指令分析模块103 ;另外,所述UI模块102还用于接收所述搜索模块104 返回的搜索结果,并将所述搜索结果拼装为结果页面后,返回所述结果页面至所述web服务模块101。 [0160] The UI module 102 for receiving the web service module 101 transmits a query instruction, and sends the inquiry command to the query command analysis module 103; Further, the UI module 102 is further configured to receive the Search module 104 returns the search results, and assembled as a result of the search results page, return to the results page to the web service module 101.

[0161] 所述需求意图分析模块103用于调用所述知识库106、用户历史行为库107,以及所述表达模板库108,以对接收到的查询指令进行需求意图分析,明确所述查询指令的需求意图。 [0161] The intention demand analysis module 103 calls for the knowledge base 106, user behavior history database 107, and the expression template database 108, the instruction to check the received demand intent analysis, clear the query command It demands intentions. 在本发明中,所述意图分析模块103首先通过所述用户历史行为库107给所述知识库106中的各个知识片段的各个需求意图打分,具体的:用户在查询某类需求时,会点击相应的满足他需求的结果,如用户想获得汽车报价相关的信息,在搜索引擎输入查询指令“朗逸”后,会点击搜索引擎返回的汽车网站的tol,如“网易车库”,此时用户输入的查询指令“朗逸”片段以及用户点击的tol “网易车库”都隐含反映用户有找车相关信息的需求,基于这一点,本发明在计算各个知识片段的需求意图时,根据某个知识片段点击某类tol的数目/某个知识片段点击的总tol,来确定此知识片段需求意图的得分,如在所述用户历史行为库107中得知,查询指令为“朗逸”,其点击的总Url数为10个,其中,商品类tol为5 个,新闻类Url为3个,图片类Url为2个,则可计算出该查询指令的商品类的需求意图为0. 5,新闻类的需求意图为0. 3,图片类的需求意图为0. 2 ;其次,在接收到用户输入的一个查询指令后,需要经过知识库106的知识匹配,得到所述查询指令中存在于所述知识库106 中的知识片段,并综合计算所述查询指令的知识库整体需求强度。 In the present invention, the intent of the analysis module 103 first historical behavior of the user library by 107 to 106 individual pieces of knowledge of the various needs of the knowledge base intent scoring, specifically: the user when querying certain requirements will click the corresponding results meet his needs, such as the user wants to get car quotes related information, enter a query in the search engine command "Sunny", the search engine returns will click tol car site, such as "NetEase garage", then the user input Query command "Sunny" fragment and the user clicks tol "NetEase garage" implicitly reflect user needs to find a car-related information, based on this, the present invention in the calculation of the various pieces of knowledge of the intent requirement, based on a knowledge fragment Click on the number of certain types of tol / a knowledge fragment clicking total tol, to determine the needs of the knowledge fragments score intent, as the user behavior history database 107 that the query command is "Sunny", the click of the total Url number 10, which is five commodity tol, news Url to 3, Picture categories Url to 2, you can calculate the intent of the query command commodity demand is 0.5, news category Demand intended to 0.3, the demand for the meaning of the picture class 0.2; Second, after receiving a query command input by the user, through knowledge required knowledge base for 106 to give the query instruction is present in the knowledge Library 106 pieces of knowledge, and comprehensive knowledge base to calculate the query command overall demand strength. 例如用户输入“上海大众朗逸报价”,则通过知识库可获得“上海大众” “朗逸”的知识片段。 For example, the user enters "Shanghai Volkswagen Lavida quote," Knowledge can be obtained through the "Shanghai Volkswagen" "Sunny" knowledge fragments. 获得初步信息后,首先将知识片段“上海大众”和“朗逸”各自的需求意图得分加总,得到第一分数,其次,再通过知识片段“上海大众”与“朗逸”的关系,加减所述第一分数,得到知识库整体需求得分, 在本发明最佳实施方式中,若知识片段的关系为同属关系,则加分;若知识片段为非同属关系,则减分;若该知识库整体需求得分大于设定的阈值,则以知识库整体需求得分最高的需求类型作为查询指令的需求意图,并根据所述需求意图在所述查询指令中加入相应的tag 信息,例如“商品”、“新闻”、“图片”等。 After obtaining preliminary information, first pieces of knowledge, "Shanghai Volkswagen" and "Sunny" intention score their needs are summed to obtain a first fraction, and secondly, through the knowledge fragment Relations "Shanghai Volkswagen" and "Sunny", the subtraction of the said first fraction to obtain knowledge score overall demand, in the preferred embodiment of the present invention, if the relationship between knowledge fragments to belong to the relationship, then add points; if knowledge fragments belong to a non-relationship, the less points; if the knowledge base overall demand is greater than the set threshold score, places the highest score overall demand knowledge requirement type as the query command needs intent, and add the appropriate tag information in the query command in accordance with the needs of intent, such as "commodity" "News", "picture", etc. 值得一提的是:在本发明的最佳实施方式中,除了计算知识库整体需求得分外,在分析需求意图时,还会考虑表达模板层面上的打分:在接收到用户输入的一个查询指令后,需要经过表达模板库108的表达模板匹配,得到所述查询指令中存在于所述表达模板库108中的表达模板片段,例如用户输入“上海大众朗逸报价”, 则通过用户模板识别出查询指令中存在的“XX报价”模板。 It is worth mentioning: In the preferred embodiment of the present invention, in addition to overall demand computing knowledge base score, but in the analysis of the intent requirement, will be considered at the level of scoring template expression: Upon receipt of a query entered by the user After the instruction, the need to go through the expression of template matching expression template library 108, to give instruction in the query expression is present in the template library 108 expression template fragments, such as the user enters "Shanghai Volkswagen Lavida quote," the template identified by the user Existing query command "XX Watch" template. 在根据上述方法获得知识库整体需求得分的同时,查询指令又符合用户需求模板,表达模板库108也对所述查询指令在表达模板层面上进行打分,得到表达模板得分,则整体查询指令的需求强度得分为知识库整体需求得分与表达模板得分的加权之和,若该加权之和大于设定的阈值,则已加权之和最大的需求类型作为查询指令的需求意图,并根据所述需求意图在所述查询指令中加入相应的tag信息,例如“商品”、“新闻”、“图片”等。 While the overall demand for knowledge score obtained by the above method, the inquiry order and consistent with the needs of users template expression template library 108 to the inquiry at the express instruction scoring template level, to give expression template score, the overall query requirements directive intensity score of knowledge and expression templates score overall demand weighted sum of scores, if the weighted sum is greater than the set threshold, already weighted sum of the maximum demand type as demand intention query command, and according to the needs of intent adding the corresponding tag information in the query instructions, such as "goods", "News", "picture", etc.

[0162] 所述结构分类模块104用于结合所述知识库106,对经过所述需求意图分析模块103后的查询指令进行智能化变换后发送至所述搜索模块105,其中,所述智能化变换即是语义内容扩充,所述的语义内容扩充包括了语义内容的归一化,以及语义类别的扩展。 [0162] The structure used to bind the classification module repository 104 106, after the query command for the intention demand analysis module 103 intelligently after conversion is sent to the search module 105, wherein said intelligent That transformation is the semantic content of the expansion, the semantic content of the expansion includes normalization, and extended semantic categories semantic content. 具体的,在所述查询指令有同属关系(上位属性的知识片段+下位属性的知识片段)时,例如, 所述查询指令为“手机诺基亚”,此时,所述结构分类模块104在发送给所述搜索模块105 时,即会在“手机”这个上位属性的知识片段上加入“可以丢弃”的tag,这样,在搜索模块105对所述查询指令进行搜索时,即可通过“手机诺基亚”进行搜索,也可通过“诺基亚”进行搜索,且还可认为带有“手机诺基亚”文本信息的网页和只带有“诺基亚”文本信息的网页权值一样;另外,例如:若所述查询指令为“诺基亚”,则所述结构分类模块104在发送给所述搜索模块105时,还可根据“诺基亚”对应其上位属性进行扩展,如扩展为“手机”,这样,在搜索模块105对“诺基亚”进行搜索时,可根据结果的数量判断是否需要扩展到“手机”进行搜索,如通过“诺基亚”搜索到的结果数量较小时,即可扩展到“手机”;又如:若所述查询指令为“手机”,则所述结构分类模块104可将“手机”对应其同位属性进行扩展,如扩展为“电脑”,这样的扩展可用于广告的推广,如在搜索页面的右侧即可根据“手机”这个查询指令进行广告推广,又可根据“电脑”这个查询指令进行广告推广;再如,若所述查询指令为“诺基亚”,则所述结构分类模块104在发送给所述搜索模块105时,还可根据“诺基亚” 对应其下位属性进行扩展,如扩展为“N71”、“N72”等,这样,在搜索模块105在搜索到带有“Ν71”、“Ν72”等文本信息网页时,也可根据这些网页的权值,判断是否作为搜索结果输出。 Specifically, in the query command there belong Relations (pieces of knowledge host attribute + lower property knowledge fragments), for example, the query instruction to "Nokia" At this point, the structural classification module 104 is sent to the The search module 105, which will be added on the pieces of knowledge "mobile" This host properties "can be discarded" tag, you so that when the search module 105 pairs of the query command to search, you can through the "Nokia" search, but also by "Nokia" search, and may also believe that with the "Nokia" page and only with the "Nokia" text on the page, like weights text information; in addition, for example: if the query commands as "Nokia", then the structural classification module 104 is sent to the search module 105 can also be expanded as "Nokia" corresponds to its host property, such as extended as "mobile phone", so that the search module 105 on the " Nokia "When searching, according to the number of results to determine whether to extend" mobile phone "searches, such as through the" Nokia "search results to a smaller number, they can be extended to" phone "; Another example: if the query Directive as "mobile phone", then the structure classification module 104 may be "mobile" corresponds to extend its co-located properties, such as extended as "computer", such extensions can be used to promote advertising, such as the right side of the search page to According to the "mobile phone" query instructions advertising, but also according to the "computer" query instructions advertising; another example, if the query command is "Nokia", then the structural classification module 104 is sent to the search module 105 can also be expanded as "Nokia" corresponds to its lower property, such as extended as "N71", "N72" and so on, so that the search module 105 in the search with the "Ν71", "Ν72" and other text information Web page can also be based on the weight of these pages, it is determined whether the output as a search result. 这种权值判断可参现有搜索引擎中的权值判断,在此不再赘述。 This weight is determined to participate in existing search engine weights judgment, are not discussed here. 总而言之,对所述查询指令进行扩展时,可根据搜索的策略,即可扩展其上位属性的知识片段,也可扩展其同位属性的知识片段,也可扩展其下位属性的知识片段。 In short, when the query command extended, according to the search strategy, you can extend the knowledge of its upper segment attributes can also be extended with the position of its knowledge fragment property, but also to expand its knowledge of the lower segment attributes.

[0163] 所述搜索模块105用于接收经过所述需求意图分析模块103或所述结构分类模块104的智能化变换后的查询指令,并将该查询指令在网页存储库110中搜索,以得到搜索结果,同时,所述搜索模块105还用于将所述搜索结果返回至所述UI模块102。 [0163] The search module 105 for receiving the intent of the requirement analysis module 103 or the structural classification module 104 intelligent transformed query commands, and the search query instructions on the page repository 110, to give search results while the search module 105 is also used for the search result is returned to the UI module 102.

[0164] 所述知识库106用于存储先验知识。 [0164] The knowledge base 106 for storing a priori knowledge. 在本发明最佳实施方式中,所述知识库主要存储为树形结构,对每一类知识库构建一棵知识库树,通过该知识库树的父亲节点标识其上位属性,右兄弟节点表示其同位属性,左兄弟节点表示其下位属性,如此迭代,直至叶子节点。 In the preferred embodiment of the present invention, the primary storage repository for the tree, the tree of knowledge to build a tree for each class knowledge base, identify its host property by the father node of the knowledge base of the tree, right-sibling representation its same position properties, left sibling express its lower property, so iterations, until the leaf nodes. 如图6所示,“大众”为其最上位属性;其下位属性为“上海大众”;与所述“上海大众” 同位的有“一汽大众”;在所述“上海大众”下位的有“朗逸”,与所述“朗逸”同位的有“途 , The "public" property to its uppermost in Figure 6; its lower property to "Shanghai Volkswagen"; a "FAW-Volkswagen" and the "Shanghai Volkswagen" with the bit; in the "Shanghai Volkswagen" has a lower " Sunny ", with the" Sunny "with bits of" way

观”......这种知识库的构建方法,本领域的普通技术人员可参现有技术完成,在此不再赘述。 View "...... method of constructing such a knowledge base, one of ordinary skill in the art can participate in the completion of the prior art, are not discussed here.

[0165] 用户历史行为库107用于存储用户历史搜索记录。 [0165] user behavior history database 107 is used to store user search history records. 优选地,其可包括查询指令、查询次数,以及加权点击数等信息。 Preferably, it may include query instructions, queries, and the weighted number of clicks and other information.

[0166] 表达模板挖掘模块108用于根据所述知识库106中的知识片段和所述用户历史行为库107中的用户历史查询指令,挖掘出表达模板,并将所述表达模板存储于所述表达模板库109中。 [0166] The expression template for mining module 108 according to the knowledge base 106 pieces of knowledge and historical behavior of the user 107 user history database query commands, dig out the expression template, and the template stored in the expression Expression template library 109. 相同需求的用户,在表达方式上会出现相似性,所述表达模板是指,一般用户在有一定查询需求时,其输入的查询指令为何,例如,当用户在查询汽车相关信息时,表达方式会有:“速腾怎么样”、“马六动力如何”等,其中即可抽取出“【汽车品牌/型号】怎么样”、“【汽车品牌/型号】动力如何”等表达汽车需求时常用的表达模板。 Users with the same demand on the expression appears similar, template refers to the average user needs when there is a certain query, the query command input of why, for example, when a user queries automobile-related information, the expression of the expression there will be: "Sagitar how", "horse power six how to" and so on, which can be extracted "[car make / model] how", "[car make / model] power how" and other commonly used when expressed demand for cars Expression templates. 在本发明的一实施方式中,具体为:首先在所述用户历史行为库107中包含知识库106知识片段的查询指令抽取出来,如在“马六如何”、“斯柯达如何”、“速腾如何”的查询指令中,抽取出知识片段:“马六”、“斯柯达”、“速腾”,其次将知识库片段替换成“【汽车品牌/型号】”符号,即生成“【汽车品牌/型号】如何”的候选表达模板;再次,统计生成的候选表达模板符合的知识库片段的数量,若该数量大于设定的阈值,则将所述候选表达模板作为表达模板,存于所述表达模板库109中;若该数量小于设定的阈值,则舍弃所述候选表达模板。 In one embodiment of the present invention, in particular: first included in the user behavior history database query command 107 Knowledge 106 knowledge fragments extracted, such as in the "six horses how to", "Skoda how ',' how Sagitar "query instruction, extracted pieces of knowledge:" Ma Six "," Skoda "," Sagitar ", followed by the fragment to replace Knowledge" [car make / model] "symbol, which generated" [car make / model] how to "express candidate template; again, the number of candidates statistics generation expression template matching knowledge base fragment, if the amount is greater than the set threshold, then the candidate as an expression of the expression template template stored in the expression template library 109; If the amount is less than the set threshold, the candidate is discarded expression template.

[0167] 所述表达模板库109用于存储由所述表达模板挖掘模块108挖掘出的表达模板。 [0167] The expression of the template library 109 for storing the expression template mining module 108 excavated expression templates.

[0168] 所述网页存储库110用于存储网页数据和该网页数据的索引信息。 [0168] The web page 110 store data for the index information stored pages and the page data. 该数据库即是普通搜索引擎常用的数据库,在此不再赘述。 The database that is normal search engine common database, will not repeat them here.

[0169] 如图3所示,在本发明第二实施方式中,所述搜索引擎包括了web服务模块101、 与web服务模块101交互通信的UI模块102、与所述UI模块102通信的需求意图分析模块103、与所述需求意图分析模块103通信的结构分析模块104、与所述结构分析模块104通信的搜索模块105,以及与所述需求意图分析模块103、所述结构分析模块104交互通信的知识库106、与所述知识库106通信的用户历史行为库107、与所述知识库106、用户历史行为库107通信的表达模板挖掘模块108、与所述表达模板挖掘模块108和所述需求意图分析模块103通信的表达模板库109,以及与所述搜索模块105通信的网页存储库110、第一垂直 [0169] FIG. 3, in the second embodiment of the present invention, shown in the search engine includes web service module 101, 102, the UI module 102 and the communication needs of the UI module and the web service communication module 101 interacts Intent Analysis module 103, 103 communicate the intent of the requirement analysis module and the structural analysis module 104, the search module 104 of the structural analysis module 105 in communication, and with the intent requirement analysis module 103, the structure interaction analysis module 104 Knowledge communication 106, and user behavior history database 106 to communicate the knowledge base 107, and the knowledge base 106, the expression template library historical behavior mining module user communication 108 107, and the expression template mining module 108 and the Expression of intent template library said demand analysis module 103 communication 109, and the web store communication and the search module 105 110, the first vertical

搜索数据111a、第二垂直搜索数据库Illb........第N垂直搜索数据库llln。 Search data 111a, a second vertical search databases Illb ........ first N vertical search databases llln. 值得一提 It is worth mentioning

的是,这些模块即可存储并运行于同一服务器中,也可存储并运行在多台服务器中。 , These modules can be stored and run on the same server, can also be stored and run on multiple servers.

[0170] 所述web服务模块101用于通过网络协议接收从客户端20传来的查询指令,并将该查询指令转到UI模块102,另外,该web服务模块101还用于接收所述UI模块102返回的结果页面,并将所述结果页面返回至客户端20。 [0170] The web service module 101 for receiving a query command 20 coming from the client through the network protocol, and the query instruction to the UI module 102, In addition, the web service module 101 is further configured to receive the UI module 102 returns the result page and the results page returned to the client 20.

[0171] 所述UI模块102用于接收所述web服务模块101传送的查询指令,并将该查询指令发送至所述查询指令分析模块103 ;另外,所述UI模块102还用于接收所述搜索模块104 返回的搜索结果,并将所述搜索结果拼装为结果页面后,返回所述结果页面至所述web服务模块101。 [0171] The UI module 102 for receiving the web service module 101 transmits a query instruction, and sends the inquiry command to the query command analysis module 103; Further, the UI module 102 is further configured to receive the Search module 104 returns the search results, and assembled as a result of the search results page, return to the results page to the web service module 101.

[0172] 所述需求意图分析模块103用于调用所述知识库106、用户历史行为库107,以及所述表达模板库108,以对接收到的查询指令进行需求意图分析,明确所述查询指令的需求意图。 [0172] The intention demand analysis module 103 calls for the knowledge base 106, user behavior history database 107, and the expression template database 108, the instruction to check the received demand intent analysis, clear the query command It demands intentions. 在本发明中,所述意图分析模块103首先通过所述用户历史行为库107给所述知识库106中的各个知识片段的各个需求意图打分,具体的:用户在查询某类需求时,会点击相应的满足他需求的结果,如用户想获得汽车报价相关的信息,在搜索引擎输入查询指令“朗逸”后,会点击搜索引擎返回的汽车网站的tol,如“网易车库”,此时用户输入的查询指令“朗逸”片段以及用户点击的tol “网易车库”都隐含反映用户有找车相关信息的需求,基于这一点,本发明在计算各个知识片段的需求意图时,根据某个知识片段点击某类tol的数目/某个知识片段点击的总此1,来确定此知识片段需求意图的得分,如在所述用户历史行为库107中得知,查询指令为“朗逸”,其点击的总Url数为10个,其中,商品类tol为5 个,新闻类Url为3个,图片类Url为2个,则可计算出该查询指令的商品类的需求意图为0. 5,新闻类的需求意图为0. 3,图片类的需求意图为0. 2 ;其次,在接收到用户输入的一个查询指令后,需要经过知识库106的知识匹配,得到所述查询指令中存在于所述知识库106 中的知识片段,并综合计算所述查询指令的知识库整体需求强度。 In the present invention, the intent of the analysis module 103 first historical behavior of the user library by 107 to 106 individual pieces of knowledge of the various needs of the knowledge base intent scoring, specifically: the user when querying certain requirements will click the corresponding results meet his needs, such as the user wants to get car quotes related information, enter a query in the search engine command "Sunny", the search engine returns will click tol car site, such as "NetEase garage", then the user input Query command "Sunny" fragment and the user clicks tol "NetEase garage" implicitly reflect user needs to find a car-related information, based on this, the present invention in the calculation of the various pieces of knowledge of the intent requirement, based on a knowledge fragment Click on the number of certain types of tol / a knowledge fragment Click total this 1 to determine the needs of the knowledge fragments score intent, as the user behavior history database 107 that the query command is "Sunny", the click Url total number of 10, which is five commodity tol, news Url to 3, Picture categories Url to 2, you can calculate the intent of the query command commodity demand is 0.5, news requirements are intended to be 0.3, the demand for the meaning of the picture class 0.2; Second, after receiving a query command input by the user, through knowledge required knowledge base for 106 to give the query instruction is present in the Knowledge 106 pieces of knowledge, and comprehensive knowledge base to calculate the query command overall demand strength. 例如用户输入“上海大众朗逸报价”,则通过知识库可获得“上海大众” “朗逸”的知识片段。 For example, the user enters "Shanghai Volkswagen Lavida quote," Knowledge can be obtained through the "Shanghai Volkswagen" "Sunny" knowledge fragments. 获得初步信息后,首先将知识片段“上海大众”和“朗逸”各自的需求意图得分加总,得到第一分数,其次,再通过知识片段“上海大众”与“朗逸”的关系,加减所述第一分数,得到知识库整体需求得分, 在本发明最佳实施方式中,若知识片段的关系为同属关系,则加分;若知识片段为非同属关系,则减分;若该知识库整体需求得分大于设定的阈值,则以知识库整体需求得分最高的需求类型作为查询指令的需求意图,并根据所述需求意图在所述查询指令中加入相应的tag 信息,例如“商品”、“新闻”、“图片”等。 After obtaining preliminary information, first pieces of knowledge, "Shanghai Volkswagen" and "Sunny" intention score their needs are summed to obtain a first fraction, and secondly, through the knowledge fragment Relations "Shanghai Volkswagen" and "Sunny", the subtraction of the said first fraction to obtain knowledge score overall demand, in the preferred embodiment of the present invention, if the relationship between knowledge fragments to belong to the relationship, then add points; if knowledge fragments belong to a non-relationship, the less points; if the knowledge base overall demand is greater than the set threshold score, places the highest score overall demand knowledge requirement type as the query command needs intent, and add the appropriate tag information in the query command in accordance with the needs of intent, such as "commodity" "News", "picture", etc. 值得一提的是:在本发明的最佳实施方式中,除了计算知识库整体需求得分外,在分析需求意图时,还会考虑表达模板层面上的打分:在接收到用户输入的一个查询指令后,需要经过表达模板库108的表达模板匹配,得到所述查询指令中存在于所述表达模板库108中的表达模板片段,例如用户输入“上海大众朗逸报价”, 则通过用户模板识别出查询指令中存在的“XX报价”模板。 It is worth mentioning: In the preferred embodiment of the present invention, in addition to overall demand computing knowledge base score, but in the analysis of the intent requirement, will be considered at the level of scoring template expression: Upon receipt of a query entered by the user After the instruction, the need to go through the expression of template matching expression template library 108, to give instruction in the query expression is present in the template library 108 expression template fragments, such as the user enters "Shanghai Volkswagen Lavida quote," the template identified by the user Existing query command "XX Watch" template. 在根据上述方法获得知识库整体需求得分的同时,查询指令又符合用户需求模板,表达模板库108也对所述查询指令在表达模板层面上进行打分,得到表达模板得分,则整体查询指令的需求强度得分为知识库整体需求得分与表达模板得分的加权之和,若该加权之和大于设定的阈值,则已加权之和最大的需求类型作为查询指令的需求意图。 While the overall demand for knowledge score obtained by the above method, the inquiry order and consistent with the needs of users template expression template library 108 to the inquiry at the express instruction scoring template level, to give expression template score, the overall query requirements directive intensity score of knowledge and expression templates score overall demand weighted sum of scores, if the weighted sum is greater than the set threshold, already weighted sum of the maximum demand type as demand intention query command.

[0173] 所述结构分类模块104用于结合所述知识库106,对经过所述需求意图分析模块103后的查询指令进行智能化变换后发送至所述搜索模块105,其中,所述智能化变换即是语义内容扩充,所述的语义内容扩充包括了语义内容的归一化,以及语义类别的扩展。 [0173] The structure used to bind the classification module repository 104 106, after the query command for the intention demand analysis module 103 intelligently after conversion is sent to the search module 105, wherein said intelligent That transformation is the semantic content of the expansion, the semantic content of the expansion includes normalization, and extended semantic categories semantic content. 具体的,在所述查询指令有同属关系(上位属性的知识片段+下位属性的知识片段)时,例如, 所述查询指令为“手机诺基亚”,此时,所述结构分类模块104在发送给所述搜索模块105 时,即会在“手机”这个上位属性的知识片段上加入“可以丢弃”的tag,这样,在搜索模块105对所述查询指令进行搜索时,即可通过“手机诺基亚”进行搜索,也可通过“诺基亚”进行搜索,且还可认为带有“手机诺基亚”文本信息的网页和只带有“诺基亚”文本信息的网页权值一样;另外,例如:若所述查询指令为“诺基亚”,则所述结构分类模块104在发送给所述搜索模块105时,还可根据“诺基亚”对应其上位属性进行扩展,如扩展为“手机”,这样,在搜索模块105对“诺基亚”进行搜索时,可根据结果的数量判断是否需要扩展到“手机”进行搜索,如通过“诺基亚”搜索到的结果数量较小时,即可扩展到“手机”;又如:若所述查询指令为“手机”,则所述结构分类模块104可将“手机”对应其同位属性进行扩展,如扩展为“电脑”,这样的扩展可用于广告的推广,如在搜索页面的右侧即可根据“手机”这个查询指令进行广告推广,又可根据“电脑”这个查询指令进行广告推广;再如,若所述查询指令为“诺基亚”,则所述结构分类模块104在发送给所述搜索模块105时,还可根据“诺基亚” 对应其下位属性进行扩展,如扩展为“N71”、“N72”等,这样,在搜索模块105在搜索到带有“Ν71”、“Ν72”等文本信息网页时,也可根据这些网页的权值,判断是否作为搜索结果输出。 Specifically, in the query command there belong Relations (pieces of knowledge host attribute + lower property knowledge fragments), for example, the query instruction to "Nokia" At this point, the structural classification module 104 is sent to the The search module 105, which will be added on the pieces of knowledge "mobile" This host properties "can be discarded" tag, you so that when the search module 105 pairs of the query command to search, you can through the "Nokia" search, but also by "Nokia" search, and may also believe that with the "Nokia" page and only with the "Nokia" text on the page, like weights text information; in addition, for example: if the query commands as "Nokia", then the structural classification module 104 is sent to the search module 105 can also be expanded as "Nokia" corresponds to its host property, such as extended as "mobile phone", so that the search module 105 on the " Nokia "When searching, according to the number of results to determine whether to extend" mobile phone "searches, such as through the" Nokia "search results to a smaller number, they can be extended to" phone "; Another example: if the query Directive as "mobile phone", then the structure classification module 104 may be "mobile" corresponds to extend its co-located properties, such as extended as "computer", such extensions can be used to promote advertising, such as the right side of the search page to According to the "mobile phone" query instructions advertising, but also according to the "computer" query instructions advertising; another example, if the query command is "Nokia", then the structural classification module 104 is sent to the search module 105 can also be expanded as "Nokia" corresponds to its lower property, such as extended as "N71", "N72" and so on, so that the search module 105 in the search with the "Ν71", "Ν72" and other text information Web page can also be based on the weight of these pages, it is determined whether the output as a search result. 这种权值判断可参现有搜索引擎中的权值判断,在此不再赘述。 This weight is determined to participate in existing search engine weights judgment, are not discussed here. 总而言之,对所述查询指令进行扩展时,可根据搜索的策略,即可扩展其上位属性的知识片段,也可扩展其同位属性的知识片段,也可扩展其下位属性的知识片段。 In short, when the query command extended, according to the search strategy, you can extend the knowledge of its upper segment attributes can also be extended with the position of its knowledge fragment property, but also to expand its knowledge of the lower segment attributes.

[0174] 所述搜索模块105用于接收经过所述需求意图分析模块103或所述结构分类模块104的智能化变换后的查询指令,并将该查询指令在多个垂直搜索数据库(第一垂直搜索 [0174] The search module 105 for receiving the intent of the requirement analysis module 103 or the structural classification module 104 intelligent transformed query commands, and the query commands in multiple vertical search databases (first vertical search for

数据库111a、第二垂直搜索数据库Illb........第N垂直数据库llln)的其中之一,以及 Database 111a, a second vertical search databases Illb ........ first N vertical database llln) of one of them, and

所述网页存储库1110中搜索,以得到搜索结果,同时,所述搜索模块105还用于将所述搜索结果返回至所述UI模块102。 The web store 1110 searches to obtain search results while the search module 105 is also used for the search result is returned to the UI module 102. 值得一提的是:选择某个垂直搜索数据库进行垂直搜索是通过查询指令的需求意图确定的,例如:若查询指令的需求意图为“商品”,则在商品垂直搜索数据库中进行搜索;所查询指令的需求意图为“图片”,则在图片垂直搜索数据库中进行搜索,其中,在垂直搜索数据库中搜索到的一条或多条结果,会插入至在网页存储库中搜索到的结果中,形成整体搜索结果。 It is worth mentioning: select a vertical search databases vertical search query instructions by intent requirements identified, for example: If the query command is intended to demand "commodity", the search in the commodity vertical search database; the query Demand intent instruction is "image", the search in the picture vertical search databases, which search vertical search databases to one or more results on the page will be inserted to search the repository to result in the formation of overall search results. 所述垂直搜索,即是在某个特定的类别下进行搜索,其具体的搜索方法和系统在本领域中已多有现有技术揭示,在此不再赘述。 The vertical search, which is carried out under a specific category search, specific search methods and systems in this field has been more than a prior art discloses, not repeat them here.

[0175] 所述知识库106用于存储先验知识。 [0175] The knowledge base 106 for storing a priori knowledge. 在本发明最佳实施方式中,所述知识库主要存储为树形结构,对每一类知识库构建一棵知识库树,通过该知识库树的父亲节点标识其上位属性,右兄弟节点表示其同位属性,左兄弟节点表示其下位属性,如此迭代,直至叶子节点。 In the preferred embodiment of the present invention, the primary storage repository for the tree, the tree of knowledge to build a tree for each class knowledge base, identify its host property by the father node of the knowledge base of the tree, right-sibling representation its same position properties, left sibling express its lower property, so iterations, until the leaf nodes. 如图6所示,“大众”为其最上位属性;其下位属性为“上海大众”;与所述“上海大众” 同位的有“一汽大众”;在所述“上海大众”下位的有“朗逸”,与所述“朗逸”同位的有“途 , The "public" property to its uppermost in Figure 6; its lower property to "Shanghai Volkswagen"; a "FAW-Volkswagen" and the "Shanghai Volkswagen" with the bit; in the "Shanghai Volkswagen" has a lower " Sunny ", with the" Sunny "with bits of" way

观”......这种知识库的构建方法,本领域的普通技术人员可参现有技术完成,在此不再赘述。[0176] 用户历史行为库107用于存储用户历史搜索记录。优选地,其可包括查询指令、查询次数,以及加权点击数等信息。 View "...... method of constructing such a knowledge base, one of ordinary skill in the art can participate in the completion of the prior art, is not described here. [0176] user behavior history database 107 is used to store user search history records Preferably, it may include query instructions, queries, and the weighted number of clicks and other information.

[0177] 表达模板挖掘模块108用于根据所述知识库106中的知识片段和所述用户历史行为库107中的用户历史查询指令,挖掘出表达模板,并将所述表达模板存储于所述表达模板库109中。 [0177] The expression template for mining module 108 according to the knowledge base 106 pieces of knowledge and historical behavior of the user 107 user history database query commands, dig out the expression template, and the template stored in the expression Expression template library 109. 相同需求的用户,在表达方式上会出现相似性,所述表达模板是指,一般用户在有一定查询需求时,其输入的查询指令为何,例如,当用户在查询汽车相关信息时,表达方式会有:“速腾怎么样”、“马六动力如何”等,其中即可抽取出“【汽车品牌/型号】怎么样”、“【汽车品牌/型号】动力如何”等表达汽车需求时常用的表达模板。 Users with the same demand on the expression appears similar, template refers to the average user needs when there is a certain query, the query command input of why, for example, when a user queries automobile-related information, the expression of the expression there will be: "Sagitar how", "horse power six how to" and so on, which can be extracted "[car make / model] how", "[car make / model] power how" and other commonly used when expressed demand for cars Expression templates. 在本发明的一实施方式中,具体为:首先在所述用户历史行为库107中包含知识库106知识片段的查询指令抽取出来,如在“马六如何”、“斯柯达如何”、“速腾如何”的查询指令中,抽取出知识片段:“马六”、“斯柯达”、“速腾”,其次将知识库片段替换成“【汽车品牌/型号】”符号,即生成“【汽车品牌/型号】如何”的候选表达模板;再次,统计生成的候选表达模板符合的知识库片段的数量,若该数量大于设定的阈值,则将所述候选表达模板作为表达模板,存于所述表达模板库109中;若该数量小于设定的阈值,则舍弃所述候选表达模板。 In one embodiment of the present invention, in particular: first included in the user behavior history database query command 107 Knowledge 106 knowledge fragments extracted, such as in the "six horses how to", "Skoda how ',' how Sagitar "query instruction, extracted pieces of knowledge:" Ma Six "," Skoda "," Sagitar ", followed by the fragment to replace Knowledge" [car make / model] "symbol, which generated" [car make / model] how to "express candidate template; again, the number of candidates statistics generation expression template matching knowledge base fragment, if the amount is greater than the set threshold, then the candidate as an expression of the expression template template stored in the expression template library 109; If the amount is less than the set threshold, the candidate is discarded expression template.

[0178] 所述表达模板库109用于存储由所述表达模板挖掘模块108挖掘出的表达模板。 [0178] The expression of the template library 109 for storing the expression template mining module 108 excavated expression templates.

[0179] 所述网页存储库110用于存储网页数据和该网页数据的索引信息。 [0179] The web page 110 store data for the index information stored pages and the page data. 该数据库即是普通搜索引擎常用的数据库,在此不再赘述。 The database that is normal search engine common database, will not repeat them here.

[0180] 所述第一垂直搜索数据库11 la、第二垂直搜索数据库Illb........第N垂直搜索 [0180] The first vertical search databases 11 la, a second vertical search databases Illb ........ first N vertical search

数据库Illn用于存储特定类别数据和该特定类别数据的索引信息,例如商品数据、商品索引;新闻数据、新闻索引;图片数据、图片索引等。 Illn database for storing information about specific categories of the index data and the specific categories of data, such as product data, commodity index; news, news indexes; image data, image indexing.

[0181] 如图4所示,在本发明第三实施方式中,所述搜索引擎包括了web服务模块101、 与web服务模块101交互通信的UI模块102、与所述UI模块102通信的需求意图分析模块103、与所述UI模块102通信的结构分析模块104、与所述结构分析模块104通信的搜索模块105,以及与所述需求意图分析模块103、所述结构分析模块104交互通信的知识库106、 与所述知识库106通信的用户历史行为库107、与所述知识库106、用户历史行为库107通信的表达模板挖掘模块108、与所述表达模板挖掘模块108和所述需求意图分析模块103通信的表达模板库109,以及与所述搜索模块105通信的网页存储库110。 [0181] In the third embodiment of the present invention, the search engine shown in Figure 4 includes web service module 101, 102, the UI module 102 and the communication needs of the UI module and the web service communication module 101 interacts Intent Analysis module 103, communication with the UI module 102 and the structural analysis module 104, the search module 104 of the structural analysis module 105 in communication, and with the intent requirement analysis module 103, the structural analysis of interactive communication module 104 Knowledge Base 106, and user behavior history database 106 to communicate the knowledge base 107, and the knowledge base 106, the expression template library historical behavior mining module user communication 108 107, and the expression template mining module 108 and the demand page 110 expression library template library 103 communicating intent analysis module 109, and 105 in communication with the search module. 值得一提的是,这些模块即可存储并运行于同一服务器中,也可存储并运行在多台服务器中。 It is worth mentioning that these modules can be stored and run on the same server, it can also be stored and run on multiple servers.

[0182] 所述web服务模块101用于通过网络协议接收从客户端20传来的查询指令,并将该查询指令转到UI模块102,另外,该web服务模块101还用于接收所述UI模块102返回的结果页面,并将所述结果页面返回至客户端20。 [0182] The web service module 101 for receiving a query command 20 coming from the client through the network protocol, and the query instruction to the UI module 102, In addition, the web service module 101 is further configured to receive the UI module 102 returns the result page and the results page returned to the client 20.

[0183] 所述UI模块102用于接收所述web服务模块101传送的查询指令,并将该查询指令发送至所述查询指令分析模块103 ;另外,所述UI模块102还用于接收所述搜索模块104 返回的搜索结果,并将所述搜索结果拼装为结果页面后,返回所述结果页面至所述web服务模块101。 [0183] The UI module 102 for receiving the web service module 101 transmits a query instruction, and sends the inquiry command to the query command analysis module 103; Further, the UI module 102 is further configured to receive the Search module 104 returns the search results, and assembled as a result of the search results page, return to the results page to the web service module 101.

[0184] 所述需求意图分析模块103用于调用所述知识库106、用户历史行为库107,以及所述表达模板库108,以对接收到的查询指令进行需求意图分析,明确所述查询指令的需求意图。 [0184] The intention demand analysis module 103 calls for the knowledge base 106, user behavior history database 107, and the expression template database 108, the instruction to check the received demand intent analysis, clear the query command It demands intentions. 在本发明中,所述意图分析模块103首先通过所述用户历史行为库107给所述知识库106中的各个知识片段的各个需求意图打分,具体的:用户在查询某类需求时,会点击相应的满足他需求的结果,如用户想获得汽车报价相关的信息,在搜索引擎输入查询指令“朗逸”后,会点击搜索引擎返回的汽车网站的tol,如“网易车库”,此时用户输入的查询指令“朗逸”片段以及用户点击的tol “网易车库”都隐含反映用户有找车相关信息的需求,基于这一点,本发明在计算各个知识片段的需求意图时,根据某个知识片段点击某类tol的数目/某个知识片段点击的总此1,来确定此知识片段需求意图的得分,如在所述用户历史行为库107中得知,查询指令为“朗逸”,其点击的总Url数为10个,其中,商品类tol为5 个,新闻类Url为3个,图片类Url为2个,则可计算出该查询指令的商品类的需求意图为0. 5,新闻类的需求意图为0. 3,图片类的需求意图为0. 2 ;其次,在接收到用户输入的一个查询指令后,需要经过知识库106的知识匹配,得到所述查询指令中存在于所述知识库106 中的知识片段,并综合计算所述查询指令的知识库整体需求强度。 In the present invention, the intent of the analysis module 103 first historical behavior of the user library by 107 to 106 individual pieces of knowledge of the various needs of the knowledge base intent scoring, specifically: the user when querying certain requirements will click the corresponding results meet his needs, such as the user wants to get car quotes related information, enter a query in the search engine command "Sunny", the search engine returns will click tol car site, such as "NetEase garage", then the user input Query command "Sunny" fragment and the user clicks tol "NetEase garage" implicitly reflect user needs to find a car-related information, based on this, the present invention in the calculation of the various pieces of knowledge of the intent requirement, based on a knowledge fragment Click on the number of certain types of tol / a knowledge fragment Click total this 1 to determine the needs of the knowledge fragments score intent, as the user behavior history database 107 that the query command is "Sunny", the click Url total number of 10, which is five commodity tol, news Url to 3, Picture categories Url to 2, you can calculate the intent of the query command commodity demand is 0.5, news requirements are intended to be 0.3, the demand for the meaning of the picture class 0.2; Second, after receiving a query command input by the user, through knowledge required knowledge base for 106 to give the query instruction is present in the Knowledge 106 pieces of knowledge, and comprehensive knowledge base to calculate the query command overall demand strength. 例如用户输入“上海大众朗逸报价”,则通过知识库可获得“上海大众” “朗逸”的知识片段。 For example, the user enters "Shanghai Volkswagen Lavida quote," Knowledge can be obtained through the "Shanghai Volkswagen" "Sunny" knowledge fragments. 获得初步信息后,首先将知识片段“上海大众”和“朗逸”各自的需求意图得分加总,得到第一分数,其次,再通过知识片段“上海大众”与“朗逸”的关系,加减所述第一分数,得到知识库整体需求得分, 在本发明最佳实施方式中,若知识片段的关系为同属关系,则加分;若知识片段为非同属关系,则减分;若该知识库整体需求得分大于设定的阈值,则以知识库整体需求得分最高的需求类型作为查询指令的需求意图,并根据所述需求意图在所述查询指令中加入相应的tag 信息,例如“商品”、“新闻”、“图片”等。 After obtaining preliminary information, first pieces of knowledge, "Shanghai Volkswagen" and "Sunny" intention score their needs are summed to obtain a first fraction, and secondly, through the knowledge fragment Relations "Shanghai Volkswagen" and "Sunny", the subtraction of the said first fraction to obtain knowledge score overall demand, in the preferred embodiment of the present invention, if the relationship between knowledge fragments to belong to the relationship, then add points; if knowledge fragments belong to a non-relationship, the less points; if the knowledge base overall demand is greater than the set threshold score, places the highest score overall demand knowledge requirement type as the query command needs intent, and add the appropriate tag information in the query command in accordance with the needs of intent, such as "commodity" "News", "picture", etc. 值得一提的是:在本发明的最佳实施方式中,除了计算知识库整体需求得分外,在分析需求意图时,还会考虑表达模板层面上的打分:在接收到用户输入的一个查询指令后,需要经过表达模板库108的表达模板匹配,得到所述查询指令中存在于所述表达模板库108中的表达模板片段,例如用户输入“上海大众朗逸报价”, 则通过用户模板识别出查询指令中存在的“XX报价”模板。 It is worth mentioning: In the preferred embodiment of the present invention, in addition to overall demand computing knowledge base score, but in the analysis of the intent requirement, will be considered at the level of scoring template expression: Upon receipt of a query entered by the user After the instruction, the need to go through the expression of template matching expression template library 108, to give instruction in the query expression is present in the template library 108 expression template fragments, such as the user enters "Shanghai Volkswagen Lavida quote," the template identified by the user Existing query command "XX Watch" template. 在根据上述方法获得知识库整体需求得分的同时,查询指令又符合用户需求模板,表达模板库108也对所述查询指令在表达模板层面上进行打分,得到表达模板得分,则整体查询指令的需求强度得分为知识库整体需求得分与表达模板得分的加权之和,若该加权之和大于设定的阈值,则已加权之和最大的需求类型作为查询指令的需求意图,并根据所述需求意图在所述查询指令中加入相应的tag信息,例如“商品”、“新闻”、“图片”等。 While the overall demand for knowledge score obtained by the above method, the inquiry order and consistent with the needs of users template expression template library 108 to the inquiry at the express instruction scoring template level, to give expression template score, the overall query requirements directive intensity score of knowledge and expression templates score overall demand weighted sum of scores, if the weighted sum is greater than the set threshold, already weighted sum of the maximum demand type as demand intention query command, and according to the needs of intent adding the corresponding tag information in the query instructions, such as "goods", "News", "picture", etc.

[0185] 所述结构分类模块104用于结合所述知识库106,对UI模块102输入的查询指令进行智能化变换后发送至所述搜索模块105,其中,所述智能化变换即是语义内容扩充,所述的语义内容扩充包括了语义内容的归一化,以及语义类别的扩展。 Send [0185] The structure used to bind the classification module repository 104 106, the input of the UI module 102 queries intelligently converted instruction to the search module 105, wherein the intelligent transformation that is the semantic content expansion, the semantic content of the expansion includes normalization, and extended semantic categories semantic content. 具体的,在所述查询指令有同属关系(上位属性的知识片段+下位属性的知识片段)时,例如,所述查询指令为“手机诺基亚”,此时,所述结构分类模块104在发送给所述搜索模块105时,即会在“手机” 这个上位属性的知识片段上加入“可以丢弃”的tag,这样,在搜索模块105对所述查询指令进行搜索时,即可通过“手机诺基亚”进行搜索,也可通过“诺基亚”进行搜索,且还可认为带有“手机诺基亚”文本信息的网页和只带有“诺基亚”文本信息的网页权值一样;另外,例如:若所述查询指令为“诺基亚”,则所述结构分类模块104在发送给所述搜索模块105时, 还可根据“诺基亚”对应其上位属性进行扩展,如扩展为“手机”,这样,在搜索模块105对“诺基亚”进行搜索时,可根据结果的数量判断是否需要扩展到“手机”进行搜索,如通过“诺基亚”搜索到的结果数量较小时,即可扩展到“手机”;又如:若所述查询指令为“手机”,则所述结构分类模块104可将“手机”对应其同位属性进行扩展,如扩展为“电脑”,这样的扩展可用于广告的推广,如在搜索页面的右侧即可根据“手机”这个查询指令进行广告推广, 又可根据“电脑”这个查询指令进行广告推广;再如,若所述查询指令为“诺基亚”,则所述结构分类模块104在发送给所述搜索模块105时,还可根据“诺基亚”对应其下位属性进行扩展,如扩展为“N71”、“N72”等,这样,在搜索模块105在搜索到带有“N71 ”、“N72”等文本信息网页时,也可根据这些网页的权值,判断是否作为搜索结果输出。 Specifically, in the query command there belong Relations (pieces of knowledge host attribute + lower property knowledge fragments), for example, the query instruction to "Nokia" At this point, the structural classification module 104 is sent to the The search module 105, which will be added on the pieces of knowledge "mobile" This host properties "can be discarded" tag, you so that when the search module 105 pairs of the query command to search, you can through the "Nokia" search, but also by "Nokia" search, and may also believe that with the "Nokia" page and only with the "Nokia" text on the page, like weights text information; in addition, for example: if the query commands as "Nokia", then the structural classification module 104 is sent to the search module 105 can also be expanded as "Nokia" corresponds to its host property, such as extended as "mobile phone", so that the search module 105 on the " Nokia "When searching, according to the number of results to determine whether to extend" mobile phone "searches, such as through the" Nokia "search results to a smaller number, they can be extended to" phone "; Another example: if the query Directive as "mobile phone", then the structure classification module 104 may be "mobile" corresponds to extend its co-located properties, such as extended as "computer", such extensions can be used to promote advertising, such as the right side of the search page to According to the "mobile phone" query instructions advertising, but also according to the "computer" query instructions advertising; another example, if the query command is "Nokia", then the structural classification module 104 is sent to the search module 105 can also be expanded as "Nokia" corresponds to its lower property, such as extended as "N71", "N72" and so on, so that the search module 105 in the search with the "N71", "N72" and other text information Web page can also be based on the weight of these pages, it is determined whether the output as a search result. 这种权值判断可参现有搜索引擎中的权值判断,在此不再赘述。 This weight is determined to participate in existing search engine weights judgment, are not discussed here. 总而言之,对所述查询指令进行扩展时,可根据搜索的策略,即可扩展其上位属性的知识片段,也可扩展其同位属性的知识片段,也可扩展其下位属性的知识片段。 In short, when the query command extended, according to the search strategy, you can extend the knowledge of its upper segment attributes can also be extended with the position of its knowledge fragment property, but also to expand its knowledge of the lower segment attributes.

[0186] 所述搜索模块105用于接收经过所述需求意图分析模块103或所述结构分类模块104的智能化变换后的查询指令,并将该查询指令在网页存储库110中搜索,以得到搜索结果,同时,所述搜索模块105还用于将所述搜索结果返回至所述UI模块102。 [0186] The search module 105 for receiving the intent of the requirement analysis module 103 or the structural classification module 104 intelligent transformed query commands, and the search query instructions on the page repository 110, to give search results while the search module 105 is also used for the search result is returned to the UI module 102.

[0187] 所述知识库106用于存储先验知识。 [0187] The knowledge base 106 for storing a priori knowledge. 在本发明最佳实施方式中,所述知识库主要存储为树形结构,对每一类知识库构建一棵知识库树,通过该知识库树的父亲节点标识其上位属性,右兄弟节点表示其同位属性,左兄弟节点表示其下位属性,如此迭代,直至叶子节点。 In the preferred embodiment of the present invention, the primary storage repository for the tree, the tree of knowledge to build a tree for each class knowledge base, identify its host property by the father node of the knowledge base of the tree, right-sibling representation its same position properties, left sibling express its lower property, so iterations, until the leaf nodes. 如图6所示,“大众”为其最上位属性;其下位属性为“上海大众”;与所述“上海大众” 同位的有“一汽大众”;在所述“上海大众”下位的有“朗逸”,与所述“朗逸”同位的有“途 , The "public" property to its uppermost in Figure 6; its lower property to "Shanghai Volkswagen"; a "FAW-Volkswagen" and the "Shanghai Volkswagen" with the bit; in the "Shanghai Volkswagen" has a lower " Sunny ", with the" Sunny "with bits of" way

观”......这种知识库的构建方法,本领域的普通技术人员可参现有技术完成,在此不再赘述。 View "...... method of constructing such a knowledge base, one of ordinary skill in the art can participate in the completion of the prior art, are not discussed here.

[0188] 用户历史行为库107用于存储用户历史搜索记录。 [0188] user behavior history database 107 is used to store user search history records. 优选地,其可包括查询指令、查询次数,以及加权点击数等信息。 Preferably, it may include query instructions, queries, and the weighted number of clicks and other information.

[0189] 表达模板挖掘模块108用于根据所述知识库106中的知识片段和所述用户历史行为库107中的用户历史查询指令,挖掘出表达模板,并将所述表达模板存储于所述表达模板库109中。 [0189] The expression template for mining module 108 according to the knowledge base 106 pieces of knowledge and historical behavior of the user 107 user history database query commands, dig out the expression template, and the template stored in the expression Expression template library 109. 相同需求的用户,在表达方式上会出现相似性,所述表达模板是指,一般用户在有一定查询需求时,其输入的查询指令为何,例如,当用户在查询汽车相关信息时,表达方式会有:“速腾怎么样”、“马六动力如何”等,其中即可抽取出“【汽车品牌/型号】怎么样”、“【汽车品牌/型号】动力如何”等表达汽车需求时常用的表达模板。 Users with the same demand on the expression appears similar, template refers to the average user needs when there is a certain query, the query command input of why, for example, when a user queries automobile-related information, the expression of the expression there will be: "Sagitar how", "horse power six how to" and so on, which can be extracted "[car make / model] how", "[car make / model] power how" and other commonly used when expressed demand for cars Expression templates. 在本发明的一实施方式中,具体为:首先在所述用户历史行为库107中包含知识库106知识片段的查询指令抽取出来,如在“马六如何”、“斯柯达如何”、“速腾如何”的查询指令中,抽取出知识片段:“马六”、“斯柯达”、“速腾”,其次将知识库片段替换成“【汽车品牌/型号】”符号,即生成“【汽车品牌/型号】如何”的候选表达模板;再次,统计生成的候选表达模板符合的知识库片段的数量,若该数量大于设定的阈值,则将所述候选表达模板作为表达模板,存于所述表达模板库109中;若该数量小于设定的阈值,则舍弃所述候选表达模板。 In one embodiment of the present invention, in particular: first included in the user behavior history database query command 107 Knowledge 106 knowledge fragments extracted, such as in the "six horses how to", "Skoda how ',' how Sagitar "query instruction, extracted pieces of knowledge:" Ma Six "," Skoda "," Sagitar ", followed by the fragment to replace Knowledge" [car make / model] "symbol, which generated" [car make / model] how to "express candidate template; again, the number of candidates statistics generation expression template matching knowledge base fragment, if the amount is greater than the set threshold, then the candidate as an expression of the expression template template stored in the expression template library 109; If the amount is less than the set threshold, the candidate is discarded expression template.

[0190] 所述表达模板库109用于存储由所述表达模板挖掘模块108挖掘出的表达模板。 [0190] The expression of the template library 109 for storing the expression template mining module 108 excavated expression templates.

[0191] 所述网页存储库110用于存储网页数据和该网页数据的索引信息。 [0191] The web page 110 store data for the index information stored pages and the page data. 该数据库即是普通搜索引擎常用的数据库,在此不再赘述。 The database that is normal search engine common database, will not repeat them here.

[0192] 如图5所示,在本发明第四实施方式中,所述搜索引擎包括了web服务模块101、 与web服务模块101交互通信的UI模块102、与所述UI模块102通信的需求意图分析模块103、与所述UI模块102通信的结构分析模块104、与所述结构分析模块104通信的搜索模块105,以及与所述需求意图分析模块103、所述结构分析模块104交互通信的知识库106、与所述知识库106通信的用户历史行为库107、与所述知识库106、用户历史行为库107通信的表达模板挖掘模块108、与所述表达模板挖掘模块108和所述需求意图分析模块103通信的表达模板库109,以及与所述搜索模块105通信的网页存储库110、第一垂直搜索数据 [0192] In a fourth embodiment of the present invention, the search engine shown in FIG. 5 includes web service module 101, 102, the UI module 102 and the communication needs of the UI module and the web service communication module 101 interacts Intent Analysis module 103, communication with the UI module 102 and the structural analysis module 104, the search module 104 of the structural analysis module 105 in communication, and with the intent requirement analysis module 103, the structural analysis of interactive communication module 104 Knowledge Base 106, and user behavior history database 106 to communicate the knowledge base 107, and the knowledge base 106, the expression template library historical behavior mining module user communication 108 107, and the expression template mining module 108 and the demand Template Library intent expression analysis module 103 communication 109, 110 communications and web repository of the search module 105, the first vertical search data

111a、第二垂直搜索数据库Illb........第N垂直搜索数据库llln。 111a, a second vertical search databases Illb ........ first N vertical search databases llln. 值得一提的是,这些 It is worth mentioning that these

模块即可存储并运行于同一服务器中,也可存储并运行在多台服务器中。 Modules can be stored and run on the same server, it can also be stored and run on multiple servers.

[0193] 所述web服务模块101用于通过网络协议接收从客户端20传来的查询指令,并将该查询指令转到UI模块102,另外,该web服务模块101还用于接收所述UI模块102返回的结果页面,并将所述结果页面返回至客户端20。 [0193] The web service module 101 for receiving a query command 20 coming from the client through the network protocol, and the query instruction to the UI module 102, In addition, the web service module 101 is further configured to receive the UI module 102 returns the result page and the results page returned to the client 20.

[0194] 所述UI模块102用于接收所述web服务模块101传送的查询指令,并将该查询指令发送至所述查询指令分析模块103 ;另外,所述UI模块102还用于接收所述搜索模块104 返回的搜索结果,并将所述搜索结果拼装为结果页面后,返回所述结果页面至所述web服务模块101。 [0194] The UI module 102 for receiving the web service module 101 transmits a query instruction, and sends the inquiry command to the query command analysis module 103; Further, the UI module 102 is further configured to receive the Search module 104 returns the search results, and assembled as a result of the search results page, return to the results page to the web service module 101.

[0195] 所述需求意图分析模块103用于调用所述知识库106、用户历史行为库107,以及所述表达模板库108,以对接收到的查询指令进行需求意图分析,明确所述查询指令的需求意图。 [0195] The intention demand analysis module 103 calls for the knowledge base 106, user behavior history database 107, and the expression template database 108, the instruction to check the received demand intent analysis, clear the query command It demands intentions. 在本发明中,所述意图分析模块103首先通过所述用户历史行为库107给所述知识库106中的各个知识片段的各个需求意图打分,具体的:用户在查询某类需求时,会点击相应的满足他需求的结果,如用户想获得汽车报价相关的信息,在搜索引擎输入查询指令“朗逸”后,会点击搜索引擎返回的汽车网站的tol,如“网易车库”,此时用户输入的查询指令“朗逸”片段以及用户点击的tol “网易车库”都隐含反映用户有找车相关信息的需求,基于这一点,本发明在计算各个知识片段的需求意图时,根据某个知识片段点击某类tol的数目/某个知识片段点击的总tol,来确定此知识片段需求意图的得分,如在所述用户历史行为库107中得知,查询指令为“朗逸”,其点击的总Url数为10个,其中,商品类tol为5 个,新闻类Url为3个,图片类Url为2个,则可计算出该查询指令的商品类的需求意图为0. 5,新闻类的需求意图为0. 3,图片类的需求意图为0. 2 ;其次,在接收到用户输入的一个查询指令后,需要经过知识库106的知识匹配,得到所述查询指令中存在于所述知识库106 中的知识片段,并综合计算所述查询指令的知识库整体需求强度。 In the present invention, the intent of the analysis module 103 first historical behavior of the user library by 107 to 106 individual pieces of knowledge of the various needs of the knowledge base intent scoring, specifically: the user when querying certain requirements will click the corresponding results meet his needs, such as the user wants to get car quotes related information, enter a query in the search engine command "Sunny", the search engine returns will click tol car site, such as "NetEase garage", then the user input Query command "Sunny" fragment and the user clicks tol "NetEase garage" implicitly reflect user needs to find a car-related information, based on this, the present invention in the calculation of the various pieces of knowledge of the intent requirement, based on a knowledge fragment Click on the number of certain types of tol / a knowledge fragment clicking total tol, to determine the needs of the knowledge fragments score intent, as the user behavior history database 107 that the query command is "Sunny", the click of the total Url number 10, which is five commodity tol, news Url to 3, Picture categories Url to 2, you can calculate the intent of the query command commodity demand is 0.5, news category Demand intended to 0.3, the demand for the meaning of the picture class 0.2; Second, after receiving a query command input by the user, through knowledge required knowledge base for 106 to give the query instruction is present in the knowledge Library 106 pieces of knowledge, and comprehensive knowledge base to calculate the query command overall demand strength. 例如用户输入“上海大众朗逸报价”,则通过知识库可获得“上海大众” “朗逸”的知识片段。 For example, the user enters "Shanghai Volkswagen Lavida quote," Knowledge can be obtained through the "Shanghai Volkswagen" "Sunny" knowledge fragments. 获得初步信息后,首先将知识片段“上海大众”和“朗逸”各自的需求意图得分加总,得到第一分数,其次,再通过知识片段“上海大众”与“朗逸”的关系,加减所述第一分数,得到知识库整体需求得分, 在本发明最佳实施方式中,若知识片段的关系为同属关系,则加分;若知识片段为非同属关系,则减分;若该知识库整体需求得分大于设定的阈值,则以知识库整体需求得分最高的需求类型作为查询指令的需求意图,并根据所述需求意图在所述查询指令中加入相应的tag 信息,例如“商品”、“新闻”、“图片”等。 After obtaining preliminary information, first pieces of knowledge, "Shanghai Volkswagen" and "Sunny" intention score their needs are summed to obtain a first fraction, and secondly, through the knowledge fragment Relations "Shanghai Volkswagen" and "Sunny", the subtraction of the said first fraction to obtain knowledge score overall demand, in the preferred embodiment of the present invention, if the relationship between knowledge fragments to belong to the relationship, then add points; if knowledge fragments belong to a non-relationship, the less points; if the knowledge base overall demand is greater than the set threshold score, places the highest score overall demand knowledge requirement type as the query command needs intent, and add the appropriate tag information in the query command in accordance with the needs of intent, such as "commodity" "News", "picture", etc. 值得一提的是:在本发明的最佳实施方式中,除了计算知识库整体需求得分外,在分析需求意图时,还会考虑表达模板层面上的打分:在接收到用户输入的一个查询指令后,需要经过表达模板库108的表达模板匹配,得到所述查询指令中存在于所述表达模板库108中的表达模板片段,例如用户输入“上海大众朗逸报价”, 则通过用户模板识别出查询指令中存在的“XX报价”模板。 It is worth mentioning: In the preferred embodiment of the present invention, in addition to overall demand computing knowledge base score, but in the analysis of the intent requirement, will be considered at the level of scoring template expression: Upon receipt of a query entered by the user After the instruction, the need to go through the expression of template matching expression template library 108, to give instruction in the query expression is present in the template library 108 expression template fragments, such as the user enters "Shanghai Volkswagen Lavida quote," the template identified by the user Existing query command "XX Watch" template. 在根据上述方法获得知识库整体需求得分的同时,查询指令又符合用户需求模板,表达模板库108也对所述查询指令在表达模板层面上进行打分,得到表达模板得分,则整体查询指令的需求强度得分为知识库整体需求得分与表达模板得分的加权之和,若该加权之和大于设定的阈值,则已加权之和最大的需求类型作为查询指令的需求意图。 While the overall demand for knowledge score obtained by the above method, the inquiry order and consistent with the needs of users template expression template library 108 to the inquiry at the express instruction scoring template level, to give expression template score, the overall query requirements directive intensity score of knowledge and expression templates score overall demand weighted sum of scores, if the weighted sum is greater than the set threshold, already weighted sum of the maximum demand type as demand intention query command.

[0196] 所述结构分类模块104用于结合所述知识库106,对UI模块102输入查询指令进行智能化变换后发送至所述搜索模块105,其中,所述智能化变换即是语义内容扩充,所述的语义内容扩充包括了语义内容的归一化,以及语义类别的扩展。 [0196] The structural classification module 104 is used in combination with the knowledge base 106, the search module 105 is sent to the rear of the UI module 102 receives the query command for intelligent transformation, wherein the transformation that is intelligent semantic content expansion , the semantic content of the expansion includes normalization, and extended semantic categories semantic content. 具体的,在所述查询指令有同属关系(上位属性的知识片段+下位属性的知识片段)时,例如,所述查询指令为“手机诺基亚”,此时,所述结构分类模块104在发送给所述搜索模块105时,即会在“手机”这个上位属性的知识片段上加入“可以丢弃”的tag,这样,在搜索模块105对所述查询指令进行搜索时,即可通过“手机诺基亚”进行搜索,也可通过“诺基亚”进行搜索,且还可认为带有“手机诺基亚”文本信息的网页和只带有“诺基亚”文本信息的网页权值一样;另外,例如:若所述查询指令为“诺基亚”,则所述结构分类模块104在发送给所述搜索模块105时,还可根据“诺基亚”对应其上位属性进行扩展,如扩展为“手机”,这样,在搜索模块105对“诺基亚” 进行搜索时,可根据结果的数量判断是否需要扩展到“手机”进行搜索,如通过“诺基亚”搜索到的结果数量较小时,即可扩展到“手机”;又如:若所述查询指令为“手机”,则所述结构分类模块104可将“手机”对应其同位属性进行扩展,如扩展为“电脑”,这样的扩展可用于广告的推广,如在搜索页面的右侧即可根据“手机”这个查询指令进行广告推广,又可根据“电脑”这个查询指令进行广告推广;再如,若所述查询指令为“诺基亚”,则所述结构分类模块104在发送给所述搜索模块105时,还可根据“诺基亚”对应其下位属性进行扩展,如扩展为“N71”、“N72”等,这样,在搜索模块105在搜索到带有“N71”、“N72”等文本信息网页时,也可根据这些网页的权值,判断是否作为搜索结果输出。 Specifically, in the query command there belong Relations (pieces of knowledge host attribute + lower property knowledge fragments), for example, the query instruction to "Nokia" At this point, the structural classification module 104 is sent to the The search module 105, which will be added on the pieces of knowledge "mobile" This host properties "can be discarded" tag, you so that when the search module 105 pairs of the query command to search, you can through the "Nokia" search, but also by "Nokia" search, and may also believe that with the "Nokia" page and only with the "Nokia" text on the page, like weights text information; in addition, for example: if the query commands as "Nokia", then the structural classification module 104 is sent to the search module 105 can also be expanded as "Nokia" corresponds to its host property, such as extended as "mobile phone", so that the search module 105 on the " Nokia "When searching, according to the number of results to determine whether to extend" mobile phone "searches, such as through the" Nokia "search results to a smaller number, they can be extended to" phone "; Another example: if the query Directive as "mobile phone", then the structure classification module 104 may be "mobile" corresponds to extend its co-located properties, such as extended as "computer", such extensions can be used to promote advertising, such as the right side of the search page to According to the "mobile phone" query instructions advertising, but also according to the "computer" query instructions advertising; another example, if the query command is "Nokia", then the structural classification module 104 is sent to the search module 105 can also be expanded as "Nokia" corresponds to its lower property, such as extended as "N71", "N72" and so on, so that the search module 105 in the search with the "N71", "N72" and other text information Web page can also be based on the weight of these pages, it is determined whether the output as a search result. 这种权值判断可参现有搜索引擎中的权值判断,在此不再赘述。 This weight is determined to participate in existing search engine weights judgment, are not discussed here. 总而言之,对所述查询指令进行扩展时,可根据搜索的策略,即可扩展其上位属性的知识片段,也可扩展其同位属性的知识片段,也可扩展其下位属性的知识片段。 In short, when the query command extended, according to the search strategy, you can extend the knowledge of its upper segment attributes can also be extended with the position of its knowledge fragment property, but also to expand its knowledge of the lower segment attributes.

[0197] 所述搜索模块105用于接收经过所述需求意图分析模块103或所述结构分类模块104的智能化变换后的查询指令,并将该查询指令在多个垂直搜索数据库(第一垂直搜索 [0197] The search module 105 for receiving the intent of the requirement analysis module 103 or the structural classification module 104 intelligent transformed query commands, and the query commands in multiple vertical search databases (first vertical search for

数据库111a、第二垂直搜索数据库Illb........第N垂直数据库llln)的其中之一,以及 Database 111a, a second vertical search databases Illb ........ first N vertical database llln) of one of them, and

所述网页存储库1110中搜索,以得到搜索结果,同时,所述搜索模块105还用于将所述搜索结果返回至所述UI模块102。 The web store 1110 searches to obtain search results while the search module 105 is also used for the search result is returned to the UI module 102. 值得一提的是:选择某个垂直搜索数据库进行垂直搜索是通过查询指令的需求意图确定的,例如:若查询指令的需求意图为“商品”,则在商品垂直搜索数据库中进行搜索;所查询指令的需求意图为“图片”,则在图片垂直搜索数据库中进行搜索,其中,在垂直搜索数据库中搜索到的一条或多条结果,会插入至在网页存储库中搜索到的结果中,形成整体搜索结果。 It is worth mentioning: select a vertical search databases vertical search query instructions by intent requirements identified, for example: If the query command is intended to demand "commodity", the search in the commodity vertical search database; the query Demand intent instruction is "image", the search in the picture vertical search databases, which search vertical search databases to one or more results on the page will be inserted to search the repository to result in the formation of overall search results. 所述垂直搜索,即是在某个特定的类别下进行搜索,其具体的搜索方法和系统在本领域中已多有现有技术揭示,在此不再赘述。 The vertical search, which is carried out under a specific category search, specific search methods and systems in this field has been more than a prior art discloses, not repeat them here.

[0198] 所述知识库106用于存储先验知识。 [0198] The knowledge base 106 for storing a priori knowledge. 在本发明最佳实施方式中,所述知识库主要存储为树形结构,对每一类知识库构建一棵知识库树,通过该知识库树的父亲节点标识其上位属性,右兄弟节点表示其同位属性,左兄弟节点表示其下位属性,如此迭代,直至叶子节点。 In the preferred embodiment of the present invention, the primary storage repository for the tree, the tree of knowledge to build a tree for each class knowledge base, identify its host property by the father node of the knowledge base of the tree, right-sibling representation its same position properties, left sibling express its lower property, so iterations, until the leaf nodes. 如图6所示,“大众”为其最上位属性;其下位属性为“上海大众”;与所述“上海大众” 同位的有“一汽大众”;在所述“上海大众”下位的有“朗逸”,与所述“朗逸”同位的有“途观”......这种知识库的构建方法,本领域的普通技术人员可参现有技术完成,在此不再赘述。 , The "public" property to its uppermost in Figure 6; its lower property to "Shanghai Volkswagen"; a "FAW-Volkswagen" and the "Shanghai Volkswagen" with the bit; in the "Shanghai Volkswagen" has a lower " Sunny ", and said" "There is an identical position" Sunny Tiguan "...... method of constructing such a knowledge base, one of ordinary skill in the art can participate in the completion of the prior art, are not discussed here.

[0199] 用户历史行为库107用于存储用户历史搜索记录。 [0199] user behavior history database 107 is used to store user search history records. 优选地,其可包括查询指令、查询次数,以及加权点击数等信息。 Preferably, it may include query instructions, queries, and the weighted number of clicks and other information.

[0200] 表达模板挖掘模块108用于根据所述知识库106中的知识片段和所述用户历史行为库107中的用户历史查询指令,挖掘出表达模板,并将所述表达模板存储于所述表达模板库109中。 [0200] The expression template for mining module 108 according to the knowledge base 106 pieces of knowledge and historical behavior of the user 107 user history database query commands, dig out the expression template, and the template stored in the expression Expression template library 109. 相同需求的用户,在表达方式上会出现相似性,所述表达模板是指,一般用户在有一定查询需求时,其输入的查询指令为何,例如,当用户在查询汽车相关信息时,表达方式会有:“速腾怎么样”、“马六动力如何”等,其中即可抽取出“【汽车品牌/型号】怎么样”、“【汽车品牌/型号】动力如何”等表达汽车需求时常用的表达模板。 Users with the same demand on the expression appears similar, template refers to the average user needs when there is a certain query, the query command input of why, for example, when a user queries automobile-related information, the expression of the expression there will be: "Sagitar how", "horse power six how to" and so on, which can be extracted "[car make / model] how", "[car make / model] power how" and other commonly used when expressed demand for cars Expression templates. 在本发明的一实施方式中,具体为:首先在所述用户历史行为库107中包含知识库106知识片段的查询指令抽取出来,如在“马六如何”、“斯柯达如何”、“速腾如何”的查询指令中,抽取出知识片段:“马六”、“斯柯达”、“速腾”,其次将知识库片段替换成“【汽车品牌/型号】”符号,即生成“【汽车品牌/型号】如何”的候选表达模板;再次,统计生成的候选表达模板符合的知识库片段的数量,若该数量大于设定的阈值,则将所述候选表达模板作为表达模板,存于所述表达模板库109中;若该数量小于设定的阈值,则舍弃所述候选表达模板。 In one embodiment of the present invention, in particular: first included in the user behavior history database query command 107 Knowledge 106 knowledge fragments extracted, such as in the "six horses how to", "Skoda how ',' how Sagitar "query instruction, extracted pieces of knowledge:" Ma Six "," Skoda "," Sagitar ", followed by the fragment to replace Knowledge" [car make / model] "symbol, which generated" [car make / model] how to "express candidate template; again, the number of candidates statistics generation expression template matching knowledge base fragment, if the amount is greater than the set threshold, then the candidate as an expression of the expression template template stored in the expression template library 109; If the amount is less than the set threshold, the candidate is discarded expression template.

[0201] 所述表达模板库109用于存储由所述表达模板挖掘模块108挖掘出的表达模板。 [0201] The expression of the template library 109 for storing the expression template mining module 108 excavated expression templates.

[0202] 所述网页存储库110用于存储网页数据和该网页数据的索引信息。 [0202] The web page 110 store data for the index information stored pages and the page data. 该数据库即是普通搜索引擎常用的数据库,在此不再赘述。 The database that is normal search engine common database, will not repeat them here.

[0203] 所述第一垂直搜索数据库111a、第二垂直搜索数据库Illb........第N垂直搜索 [0203] The first vertical search databases 111a, a second vertical search databases Illb ........ first N vertical search

数据库Illn用于存储特定类别数据和该特定类别数据的索引信息,例如商品数据、商品索引;新闻数据、新闻索引;图片数据、图片索引等。 Illn database for storing information about specific categories of the index data and the specific categories of data, such as product data, commodity index; news, news indexes; image data, image indexing.

[0204] 如图7所示,本发明第一实施方式的搜索方法包括以下步骤: [0204] As shown in Figure 7, the first embodiment of the invention comprises the steps of search:

[0205] Si、接收查询指令;优选地,该查询指令是用户通过客户端上的浏览器输入的至web服务模块101,该web服务模块101在得到所述查询命令后,会将该查询命令转到UI模块102 ; [0205] Si, receiving a query command; preferably, the query was a user input through the browser on the client to the web service module 101, the web service module 101 after receiving the query command, the query Go to the UI module 102;

[0206] S2、基于知识库对所述查询指令进行需求意图分析,明确所述查询指令的需求意图;优选地,该步骤是通过所述需求意图分析模块103完成的; [0206] S2, based on knowledge of the intention of the query instructions demand analysis, demand a clear intention of the query command; Preferably, this step is a requirement by the intention to complete the analysis module 103;

[0207] S3、将带有需求意图的所述查询指令在数据库中搜索,得到搜索结果;优选地,该步骤是通过所述搜索模块105完成的; The query command [0207] S3, the intent with demand search the database to obtain search results; Preferably, this step is performed by the search module 105 completed;

[0208] S4、输出所述搜索结果。 [0208] S4, the output of the search results. 优选地,该步骤是在所述UI模块102和所述web服务模块101中完成的,搜索结果从所述搜索模块104返回至所述UI模块102,并通过所述UI模块102将所述搜索结果拼装为结果页面后,返回所述结果页面至所述web服务模块101,从而通过所述web服务模块101返回至客户端浏览器。 Preferably, this step is performed in the UI module 102 and the web service module 101, the search results returned from the search module 104 to the UI module 102, and through the UI module 102 of the search Results assembling the results page, return to the results page to the web service module 101, so that by the web service module 101 is returned to the client browser.

[0209] 其中,在所述S3步骤中的数据库即可为网页存储库110,或与需求意图相对应的垂直搜索数据库;当然,也可包括网页存储库110和与所述需求意图相对应的垂直搜索数据库。 [0209] wherein, in the database of the step S3 to a web page repository 110, or with the intent of demand corresponding vertical search database; of course, also include a web page repository 110 may correspond to the needs and intentions vertical search databases.

[0210] 在所述S2步骤和S3步骤之间,还包括语义扩充步骤: [0210] In step between the S2 and S3 step, further comprising the step of semantic expansion:

[0211] 基于所述知识库对接收到的查询指令进行语义扩充;优选地,该步骤是通过结构分析模块104完成的。 [0211] Knowledge-based query received the instruction semantics expansion; Preferably, this step is performed by the analysis module 104 to complete the structure. [0212] 如图8所示,本发明第二实施方式的搜索方法包括以下步骤: [0212] 8, the second embodiment of the present invention as shown in the following search method comprising the steps of:

[0213] Si'、接收查询指令;优选地,该查询指令是用户通过客户端上的浏览器输入的至web服务模块101,该web服务模块101在得到所述查询命令后,会将该查询命令转到UI模块102 ; [0213] Si ', receiving a query command; preferably, the query was a user through the browser on the client's input to the web service module 101, the web service module 101 after receiving the query command, the query command to change UI module 102;

[0214] S2'、基于知识库对所述查询指令进行需求意图分析,明确所述查询指令的需求意图,同时,基于所述知识库对接收到的查询指令进行语义扩充;优选地,该步骤是通过所述需求意图分析模块103和所述结构分析模块104完成的; [0214] S2 ', based on knowledge of the intention of the query instructions demand analysis, demand a clear intention of the query command, while the Knowledge-based query instructions received semantic expansion; Preferably, the step the intention is to complete by the demand analysis module 103 and the structural analysis module 104;

[0215] S3'、将带有需求意图并扩充语义的查询指令在数据库中搜索,得到搜索结果;优选地,该步骤是通过所述搜索模块105完成的; [0215] S3 ', the intention with the demand and the expansion of semantic search query instructions in the database, get the search results; Preferably, this step is performed by the search module 105 completed;

[0216] S4'、输出所述搜索结果。 [0216] S4 ', the output of the search results. 优选地,该步骤是在所述UI模块102和所述web服务模块101中完成的,搜索结果从所述搜索模块104返回至所述UI模块102,并通过所述UI模块102将所述搜索结果拼装为结果页面后,返回所述结果页面至所述web服务模块101,从而通过所述web服务模块101返回至客户端浏览器。 Preferably, this step is performed in the UI module 102 and the web service module 101, the search results returned from the search module 104 to the UI module 102, and through the UI module 102 of the search Results assembling the results page, return to the results page to the web service module 101, so that by the web service module 101 is returned to the client browser.

[0217] 其中,在所述S3'步骤中的数据库即可为网页存储库110,或与需求意图相对应的垂直搜索数据库;当然,也可包括网页存储库110和与所述需求意图相对应的垂直搜索数据库。 [0217] wherein the database in the S3 'step to a Web page repository 110, or with the intent requirement corresponding vertical search databases; of course, also be included on the page repository 110 and corresponding to the needs of intent vertical search databases.

[0218] 如图9所示,本发明第三实施方式的搜索方法包括以下步骤: [0218] FIG 9, a third embodiment of the present invention as shown in the following search method comprising the steps of:

[0219] S10、接收查询指令;优选地,该查询指令是用户通过客户端上的浏览器输入的至web服务模块101,该web服务模块101在得到所述查询命令后,会将该查询命令转到UI模块102 ; [0219] S10, receiving a query command; preferably, the query was a user through the browser on the client's input to the web service module 101, the web service module 101 after receiving the query command, the query Go to the UI module 102;

[0220] S20、基于知识库和表达模板库对所述查询指令进行需求意图分析,明确所述查询指令的需求意图;优选地,该步骤是通过所述需求意图分析模块103完成的; [0220] S20, based on knowledge and expression template library for the query instructions intention demand analysis, demand a clear intention of the query command; Preferably, this step is a requirement by the intention to complete the analysis module 103;

[0221] S30、将带有需求意图的所述查询指令在数据库中搜索,得到搜索结果;优选地,该步骤是通过所述搜索模块105完成的; The query command [0221] S30, the intent with demand search the database to obtain search results; Preferably, this step is performed by the search module 105 completed;

[0222] S40、输出所述搜索结果。 [0222] S40, the output of the search results. 优选地,该步骤是在所述UI模块102和所述web服务模块101中完成的,搜索结果从所述搜索模块104返回至所述UI模块102,并通过所述UI模块102将所述搜索结果拼装为结果页面后,返回所述结果页面至所述web服务模块101,从而通过所述web服务模块101返回至客户端浏览器。 Preferably, this step is performed in the UI module 102 and the web service module 101, the search results returned from the search module 104 to the UI module 102, and through the UI module 102 of the search Results assembling the results page, return to the results page to the web service module 101, so that by the web service module 101 is returned to the client browser.

[0223] 其中,在所述S30步骤中的数据库即可为网页存储库110,或与需求意图相对应的垂直搜索数据库;当然,也可包括网页存储库110和与所述需求意图相对应的垂直搜索数据库。 [0223] wherein the database in the step S30 to a Web page repository 110, or with the intent requirement corresponding vertical search databases; of course, also be included on the page repository 110 and correspond to the needs of intentions vertical search databases.

[0224] 在所述S20步骤和S30步骤之间,还包括语义扩充步骤: [0224] In the step S20 and S30 between the step, further comprising the step of semantic expansion:

[0225] 基于所述知识库对接收到的查询指令进行语义扩充;优选地,该步骤是通过结构分析模块104完成的。 [0225] Knowledge-based query received the instruction semantics expansion; Preferably, this step is performed by the analysis module 104 to complete the structure.

[0226] 如图8所示,本发明第四实施方式的搜索方法包括以下步骤: [0226] 8, the fourth embodiment of the present invention as shown in the following search method comprising the steps of:

[0227] S10'、接收查询指令;优选地,该查询指令是用户通过客户端上的浏览器输入的至web服务模块101,该web服务模块101在得到所述查询命令后,会将该查询命令转到UI模块102 ; [0227] S10 ', receiving a query command; preferably, the query was a user through the browser on the client's input to the web service module 101, the web service module 101 after receiving the query command, the query command to change UI module 102;

[0228] S20'、基于知识库和表达模板库对所述查询指令进行需求意图分析,明确所述查询指令的需求意图,同时,基于所述知识库对接收到的查询指令进行语义扩充;优选地,该步骤是通过所述需求意图分析模块103和所述结构分析模块104完成的; [0228] S20 ', based on knowledge and expression template library instruction requirement of the query intent analysis, the demand for a clear intention of the query command, while the Knowledge-based query instructions received semantic expansion; preferably , this step by the intention demand analysis module 103 and the structural analysis module 104 completed;

[0229] S30'、将带有需求意图并扩充语义的查询指令在数据库中搜索,得到搜索结果;优选地,该步骤是通过所述搜索模块105完成的; [0229] S30 ', the intention with the demand and the expansion of semantic search query instructions in the database, get the search results; Preferably, this step is performed by the search module 105 completed;

[0230] S40,、输出所述搜索结果。 [0230] S40 ,, the output of the search results. 优选地,该步骤是在所述UI模块102和所述web服务模块101中完成的,搜索结果从所述搜索模块104返回至所述UI模块102,并通过所述UI 模块102将所述搜索结果拼装为结果页面后,返回所述结果页面至所述web服务模块101, 从而通过所述web服务模块101返回至客户端浏览器。 Preferably, this step is performed in the UI module 102 and the web service module 101, the search results returned from the search module 104 to the UI module 102, and through the UI module 102 of the search Results assembling the results page, return to the results page to the web service module 101, so that by the web service module 101 is returned to the client browser.

[0231] 其中,在所述S30'步骤中的数据库即可为网页存储库110,或与需求意图相对应的垂直搜索数据库;当然,也可包括网页存储库110和与所述需求意图相对应的垂直搜索数据库。 [0231] wherein the database in the S30 'to step in as a Web page repository 110, or with the intent requirement corresponding vertical search databases; of course, also be included on the page repository 110 and corresponding to the needs of intent vertical search databases.

[0232] 如图11所示,在本发明第一实施方式、第二实施方式、第三实施方式、第四实施方式的搜索方法中,所述“基于知识库对所述查询指令进行需求意图分析,明确所述查询指令的需求意图”步骤的一实施方式,包括以下流程: [0232] 11, in a first embodiment of the present invention, the second embodiment, the third embodiment, the fourth embodiment of the search method, the "knowledge base based on the intent of the query instruction needs analysis, needs a clear intention of the query command "step one embodiment, the process comprises the following:

[0233] S200、通过用户历史行为库给知识库中的各个知识片段的各个需求意图打分,使各个知识片段都具有相应的需求意图得分;具体的:用户在查询某类需求时,会点击相应的满足他需求的结果,如用户想获得汽车报价相关的信息,在搜索引擎输入查询指令“朗逸”后,会点击搜索引擎返回的汽车网站的tol,如“网易车库”,此时用户输入的查询指令“朗逸”片段以及用户点击的Url “网易车库”都隐含反映用户有找车相关信息的需求,基于这一点,本发明在计算各个知识片段的需求意图时,根据某个知识片段点击某类tol的数目/某个知识片段点击的总此1,来确定此知识片段需求意图的得分,如在所述用户历史行为库107中得知,查询指令为“朗逸”,其点击的总Url数为10个,其中,商品类to 1为5个, 新闻类Url为3个,图片类Url为2个,则可计算出该查询指令的商品类的需求意图为0. 5, 新闻类的需求意图为0. 3,图片类的需求意图为0. 2 ; [0233] S200, user behavior history database repository to the various needs of the various pieces of knowledge of the intention of scoring, so that all pieces of knowledge has a corresponding demand intention score; in particular: the user when querying certain demand will click on the corresponding The results meet his needs, such as the user wants to get car quotes related information entered in the search engine query command "Sunny", the search engine returns will click tol car site, such as "NetEase garage" At this point the user entered Query command "Sunny" fragment and the user clicks Url "NetEase garage" implicitly reflect user needs to find a car-related information, based on this, the present invention in the calculation of the various pieces of knowledge of the intent requirement, based on a knowledge fragment click tol certain number of / a knowledge fragment Click total this 1 to determine the needs of the knowledge fragments score intent, as the user behavior history database 107 that the query command is "Sunny", the click of the total Url number 10, in which commodity to 1 to 5, news Url to 3, Picture categories Url to 2, you can calculate the intent of the query command commodity demand is 0.5, news requirements are intended to be 0.3, the demand for the meaning of the picture class 0.2;

[0234] S201、在接收到用户输入的一个查询指令后,将所述查询指令与知识片段匹配,得到与所述查询指令相匹配的至少一个知识片段;例如用户输入“上海大众朗逸报价”,则通过知识库可获得“上海大众” “朗逸”的知识片段; [0234] S201, after receiving a query command the user enters the query instruction and match pieces of knowledge to give instructions to the query matches the knowledge of at least one segment; for example, the user enters "Shanghai Volkswagen Lavida quote" Knowledge can be obtained through the "Shanghai Volkswagen" "Sunny" knowledge fragment;

[0235] S202、将与所述查询指令相匹配的知识片段的需求意图得分加总,得到第一分数; 例如:知识片段“上海大众”和“朗逸”各自的需求意图得分加总,得到第一分数; [0235] S202, the intent of the query command needs to match the pieces of knowledge scores are summed to obtain a first score; for example: pieces of knowledge, "Shanghai Volkswagen" and "Sunny" intent to score their needs are summed to obtain a first a fraction;

[0236] S203、通过与所述查询指令相匹配的知识片段在所述知识库中的从属关系,加减所述第一分数,得到知识库整体需求得分;在本发明最佳实施方式中,若知识片段的关系为同属关系,则加分;若知识片段为非同属关系,则减分; [0236] S203, by the knowledge that match the query instruction fragment affiliation in the knowledge base, the addition and subtraction of the first fraction, obtained knowledge score overall demand; In a preferred embodiment of the present invention, If the relationship between knowledge fragments to belong to the relationship, then add points; if knowledge fragments belong to a non-relationship, the less points;

[0237] S204、判断所述知识库整体需求得分是否大于一设定阈值; [0237] S204, determines the overall demand knowledge score is greater than a predetermined threshold;

[0238] S205、若大于所述设定阈值,则以所述知识库整体需求得分最高的需求类型作为所述查询指令的需求意图; [0238] S205, if it exceeds the set threshold value, places the highest score overall demand for knowledge requirement type as the query command intent requirement;

[0239] S206、若小于所述设定阈值,则判断所述查询指令无明显需求意图,按照普通搜索引擎搜索方式进行搜索,在此不再赘述。 [0239] S206, if less than the set threshold value, it is determined that no significant demand for the query command intent, according to the conventional way of search engines search, not repeat them here.

[0240] 如图12所示,在本发明第一实施方式、第二实施方式、第三实施方式、第四实施方式的搜索方法中,所述“基于知识库和表达模板库对所述查询指令进行需求意图分析,明确所述查询指令的需求意图”步骤的另一实施方式,包括以下流程: [0240] FIG. 12, in the first embodiment of the invention, a second embodiment, the third embodiment, the fourth embodiment of the search method, the "Knowledge-based template library and expression of the query instruction requirement Intent Analysis, another embodiment of the intent requirement "clearly the query command procedure, including the following processes:

[0241] S200'、通过用户历史行为库给知识库中的各个知识片段的各个需求意图打分,使各个知识片段都具有相应的需求意图得分;具体的:用户在查询某类需求时,会点击相应的满足他需求的结果,如用户想获得汽车报价相关的信息,在搜索引擎输入查询指令“朗逸”后,会点击搜索引擎返回的汽车网站的tol,如“网易车库”,此时用户输入的查询指令“朗逸”片段以及用户点击的Url “网易车库”都隐含反映用户有找车相关信息的需求,基于这一点,本发明在计算各个知识片段的需求意图时,根据某个知识片段点击某类tol的数目/某个知识片段点击的总此1,来确定此知识片段需求意图的得分,如在所述用户历史行为库107中得知,查询指令为“朗逸”,其点击的总to 1数为10个,其中,商品类to 1为5个, 新闻类tol为3个,图片类tol为2个,则可计算出该查询指令的商品类的需求意图为0. 5, 新闻类的需求意图为0. 3,图片类的需求意图为0. 2 ; [0241] S200 ', by the user to the various needs of the library historical behavior of various pieces of knowledge Knowledge of intent scoring, so that all pieces of knowledge has a corresponding demand intention score; in particular: the user when querying certain requirements will click the corresponding results meet his needs, such as the user wants to get car quotes related information, enter a query in the search engine command "Sunny", the search engine returns will click tol car site, such as "NetEase garage", then the user input Query command "Sunny" fragment and the user clicks Url "NetEase garage" implicitly reflect user needs to find a car-related information, based on this, the present invention in the calculation of the various pieces of knowledge of the intent requirement, based on a knowledge fragment Click on the number of certain types of tol / a knowledge fragment Click total this 1 to determine the needs of the knowledge fragments score intent, as the user behavior history database 107 that the query command is "Sunny", the click The total number of 10 to 1, in which the commodity to 1 to 5, for the three news tol, tol picture category is two, you can calculate the intent of the query command commodity demand is 0.5, Demand intention news is 0.3, the demand for the meaning of the picture class 0.2;

[0242] S201'、在接收到用户输入的一个查询指令后,将所述查询指令与知识片段和存储于表达模板库中的表达模板匹配,得到与所述查询指令相匹配的至少一个知识片段和一个表达模板;例如用户输入“上海大众朗逸报价”,则通过知识库可获得“上海大众” “朗逸”的知识片段;通过表达模板库克获得查询指令中存在的“XX报价”的表达模板; [0242] S201 ', after receiving a query command the user enters the query expression template matching instruction and knowledge fragments and stored in the expression template library to give instructions to the query matches the knowledge of at least one segment and an expression template; for example, the user enters "Shanghai Volkswagen Lavida quote," Knowledge can be obtained through the "Shanghai Volkswagen" "Sunny" fragments of knowledge; access to query commands exist in the template by expressing Cook "XX quote" Expression Templates ;

[0243] S202'、将与所述查询指令相匹配的知识片段的需求意图得分加总,得到第一分数;例如:知识片段“上海大众”和“朗逸”各自的需求意图得分加总,得到第一分数; [0243] S202 ', the intent of the query command needs to match the pieces of knowledge scores are summed to obtain a first score; for example: pieces of knowledge, "Shanghai Volkswagen" and "Sunny" intent to score their needs are summed to give The first score;

[0244] S203'、通过与所述查询指令相匹配的知识片段在所述知识库中的从属关系,加减所述第一分数,得到知识库整体需求得分;在本发明最佳实施方式中,若知识片段的关系为同属关系,则加分;若知识片段为非同属关系,则减分; [0244] S203 ', by the knowledge that match the query instruction fragment affiliation in the knowledge base, the addition and subtraction of the first fraction, obtained knowledge score overall demand; In a preferred embodiment of the present invention, If the relation of knowledge fragments belong to the relationship, then add points; if knowledge fragments belong to a non-relationship, the less points;

[0245] S204'、对所述查询指令在表达模板层面上进行打分,得到表达模板得分; [0245] S204 ', the expression of the query command in scoring on the template level, to give expression template score;

[0246] S205'、将知识库整体需求得分与表达模板得分的加权之和作为查询指令需求强度得分; [0246] S205 ', the overall demand for knowledge and expression templates score score weighted sum of scores as the query command needs strength;

[0247] S206'、判断所述查询指令需求强度得分是否大于一设定阈值; [0247] S206 ', judges score the query command the strength of demand is greater than a predetermined threshold;

[0248] S207'、若大于所述设定阈值,则以查询指令需求强度得分最高的需求类型作为所述查询指令的需求意图; [0248] S207 ', if greater than the predetermined threshold, the query command places the highest score of the strength of demand, as the demand for the type of query command intent requirement;

[0249] S208'、若小于所述设定阈值,则判断所述查询指令无明显的需求意图。 [0249] S208 ', if less than the set threshold value, it is determined that the query command no need intent.

[0250] 如图13所示,在本发明第三实施方式、第四实施方式的搜索方法中,所述表达模板库的构建方法,包括以下流程: [0250] In the third embodiment of the present invention, a fourth embodiment of the search method, the expression of 13 template library construction method, comprising the following process:

[0251] S300、抽取在用户历史行为库中包含知识片段的查询指令;如在“马六如何”、“斯柯达如何”、“速腾如何”的查询指令中,抽取出知识片段:“马六”、“斯柯达”、“速腾”; [0251] S300, extracts the user historical behavior database query instructions contained pieces of knowledge; and if "six horses how to", "Skoda how", "Sagitar how" query command, extract the pieces of knowledge: "Six horses" "Skoda", "Sagitar";

[0252] S301、将所述知识库片段替换成通用符号,生成候选表达模板;例如:“【汽车品牌/型号】”符号,即生成“【汽车品牌/型号】如何”的候选表达模板; [0252] S301, the knowledge base fragments replace common symbols, generating a candidate expression template; for example: "[car make / model]" symbol, which generated "[car make / model] how to" express candidate template;

[0253] S302、统计生成的候选表达模板符合的知识库片段的数量; [0253] S302, the number of candidates statistics generation expression template matching knowledge fragments;

[0254] S303、判断所述数量是否大于设定的阈值; [0254] S303, determines whether the number is greater than the set threshold;

[0255] S304、若大于设定的阈值,则将所述候选表达模板作为表达模板,并存于数据库中,生成表达模板库; [0255] S304, if greater than the set threshold, the candidate of the expression as an expression template Templates and stored in the database, generating expression template library;

[0256] S305、若小于设定阈值,则舍弃所述候选表达模板。 [0256] S305, if less than the set threshold, then discarded the candidate expression template.

[0257] 通过上述的搜索方法及搜索引擎,本发明一种实施方式的在线界面如图14所示,用于在浏览器中打开本发明搜索引擎的在线界面,并在对话框中输入查询指令“手机诺基亚”,通过上述的搜索方法及搜索系统,可判断出该查询指令包括了商品类的需求意图,故在本发明的搜索方法及搜索系统中,可将“手机诺基亚”这个查询指令在商品垂直搜索数据库中进行搜索,同时,插入该垂直搜索结果至网页存储库中搜索的结果中,如图的A部分, 当用户点击所述垂直搜索结果时,即可跳转至新页面中,如图15所示,该新页面中包含了具有商品类需求意图的检索结果,从图中B部分可看出,这条检索结果中并未包括“手机” 这个文本信息,即是通过本发明的语义扩展得到的搜索结果。 [0257] The above-mentioned search methods and search engines, one embodiment of the invention of the online interface shown in Figure 14, the present invention is used to open the search engine in the browser online interface, and enter the query command in the dialog box "Nokia", by the above search methods and search system can determine the query command includes the intent commodity demand, so in search methods and search system of the present invention may be "Nokia" This query instructions Product search vertical search databases, while inserted into the vertical search results to a website repository search result, A section as shown when the user clicks on the vertical search results, you can jump to a new page, As shown, the new page in the search result contains 15 commodities demand has intention, part B can be seen from the figures, this does not include the search results, "mobile phone" in this text, that is, through the present invention The semantic extension to get search results.

[0258] 综上所述可知,本发明在知识库的基础上,更好的理解用户输入的查询指令,分析查询指令的以图,解析查询指令的结构,对查询指令进行语义内容扩充,从而更好的指导搜索引擎选择优质的资源满足用户的搜索需求,使得用户搜索效率提高,节约网络流量。 [0258] In summary above, the present invention on the basis of knowledge, a better understanding of query commands entered by the user, attempt to analyze query command parsing structure query command, query instructions semantic content expansion, which better guide the search engine to select high-quality resources to meet the user's search needs, enabling users to search for efficiency, saving network traffic.

[0259] 应当理解,虽然本说明书按照实施方式加以描述,但并非每个实施方式仅包含一个独立的技术方案,说明书的这种叙述方式仅仅是为清楚起见,本领域技术人员应当将说明书作为一个整体,各实施例中的技术方案也可以经适当组合,形成本领域技术人员可以理解的其他实施方式。 [0259] It should be understood that although the present specification are described according to the embodiment, but not every embodiment contains only a single technical solution, this narrative description only for the sake of clarity, those skilled in the art will appreciate that the specification as a Overall, the technical solutions of each example embodiments may be suitably combined to form other embodiments of the present can be understood by the skilled person.

[0260] 上文所列出的一系列的详细说明仅仅是针对本发明的可行性实施方式的具体说明,它们并非用以限制本发明的保护范围,凡未脱离本发明技艺精神所作的等效实施方式或变更均应包含在本发明的保护范围之内。 [0260] a series of detailed instructions listed above are merely a specific explanation for the feasibility embodiment of the present invention, they are not intended to limit the scope of the present invention, the equivalent who have not traveled out of the spirit of the art of the present invention made embodiments or change shall be included within the scope of the present invention.

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Klassifizierungen
Internationale KlassifikationG06F17/30
Juristische Ereignisse
DatumCodeEreignisBeschreibung
15. Juni 2011C06Publication
7. Sept. 2011C10Request of examination as to substance
16. Jan. 2013C14Granted