CA2622784A1 - Ranking blog documents - Google Patents
Ranking blog documents Download PDFInfo
- Publication number
- CA2622784A1 CA2622784A1 CA002622784A CA2622784A CA2622784A1 CA 2622784 A1 CA2622784 A1 CA 2622784A1 CA 002622784 A CA002622784 A CA 002622784A CA 2622784 A CA2622784 A CA 2622784A CA 2622784 A1 CA2622784 A1 CA 2622784A1
- Authority
- CA
- Canada
- Prior art keywords
- blog
- blog document
- document
- quality
- score
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Abandoned
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/95—Retrieval from the web
- G06F16/951—Indexing; Web crawling techniques
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/95—Retrieval from the web
- G06F16/953—Querying, e.g. by the use of web search engines
- G06F16/9538—Presentation of query results
Abstract
A blog search engine may receive a search query. The blog search engine may determine scores for a group of blog documents in response to the search query, where the scores are based on a relevance of the group of blog documents to the search query and a quality of the group of blog documents.
The blog search engine may also provide information regarding the group of blog documents based on the determined scores.
The blog search engine may also provide information regarding the group of blog documents based on the determined scores.
Description
2 PCT/US2006/035539 RANK UNG BLOG DOCUMENTS
FIELD OF THE INVENTION
Implementations consistent with the principles of the invention relate generally to information retrieval and, more particularly, to providing a ranked set of blog documents in response to search queries.
BACKGROUND OF THE INVENTION
The World Wide Web ("web") contains a vast amount of information. Locating a desired portion of the information, however, can be challenging. This problem is compounded because the amount of information on the web and the number of new users inexperienced at web searching are growing rapidly.
Search engines attempt to return hyperlinks to web pages in which a user is interested. Generally, search engines base their detennination of the user's interest on search terms (called a search query) entered by the user. The goal of the search engine is to provide links to high quality, relevant results (e.g., web pages) to the user based on the search query. Typically, the search engine accomplishes this by matching the terms hi the search query to a corpus of pre-stored web pages. Web pages that contain the user's search terms are identified as search results and are returned to the user as links.
Over the past few years, a new medium, called a blog, has appeared on the web.
Blogs (short for web logs) are publications of personal thoughts that are typically updated frequently with new journal entries, called posts. The content and quality of blogs and their posts can vary greatly depending on the purpose of the authors of the blogs. As blogging becomes more popular, the ability to provide quality blog search results becomes more important.
SUMMARY OF THE INVENTION
In accordance with one iinplementation consistent with the principles of the invention, a method may include receiving a search queiy at a blog search engnie, retrieving a blog document in response to the search query, determining a first score for the blog docunlent based on the relevance of the blog document to the search query, altering the first score based on a quality of the blog docuinent, and providing infonnation regarding the blog document based on the altered first score.
In anotlier iunplementation consistent with the principles of the invention, a computer-implemented method includes obtaining a blog document, identifying at least one of the positive indicators of a quality of the blog document or negative indicators of the quality of the blog document, and determining a quality score for the blog document based on the identified at least one of positive indicators or negative indicators.
In yet another implementation consistent with the principles of the invention, a method may include receiving a search query at a blog search engine; determining scores for a group of blog documents in response to the search query, the scores being based on a relevance of the group of blog documents to the search query and a quality of the group of blog docmnents; and providing information regarding the group of blog documents based on the determined scores.
In still another iunplementation consistent with the principles of the invention, a method may include identifying at least one of the positive indicators of a quality of a blog docuinent or negative indicators of the quality of the blog document, the identified at least one of positive indicators or negative indicators including an indicator specific to blog documents; determining a quality score for the blog document based on the identified at least one of positive indicators or negative indicators; receiving a search query; determining a score for the blog document based on a relevance of the blog document to the search query;
adjusting the score of the blog document based on the quality score; and providing information relating to the blog document based on the adjusted score.
BRIEF DESCRIPTION OF THE DRAWINGS
The accompanyhig drawings, which are incorporated in and constitute a part of this specification, illustrate an innplementation of the invention and, together with the description, explain the invention. In the drawings, Fig. I is an exeinplary diagram illustrating a concept consistent with the principles of the invention;
Fig. 2 is an exemplary diagram of a networlc in wliich systems and methods consistent with the principles of the invention inay be implemented;
Fig. 3 is an exeinplary diagrani of a client or server entity in an implementation consistent with the principles of the invention;
Fig. 4 is a diagram of a portion of an exemplaiy computer-readable medium that may be used by the server of Fig. 2;
Fig. 5 is an exeinplary database that may be associated with the server of Fig. 2 in an implementation consistent with the principles of the invention;
Fig. 6 is a flow chart of an exemplary process for determining a quality score for a blog document in an implementation consistent with the principles of the invention;
Fig. 7 is a flowchart of an exemplary process for presenting search results in an implementation consistent witli the principles of the invention; and Fig. 8 is a diagram of an exeinplary set of documents that may be retrieved in an unplementation consistent with the principles of the invention.
DETAILED DESCRIPTION
The following detailed description of implementations consistent with the principles of the invention refers to the accompanying drawings. The same reference numbers in different drawings may identify the same or similar elements. Also, the following detailed description does not limit the invention.
OVERVIEW
Systems and methods consistent with the principles of the invention improve the quality of blog results provided in response to a search query. To iunprove the quality of blog results, a number of quality factors may be used to alter (either positively or negatively) a score of the blog results.
Fig. 1 is an exemplary diagrain illustrating a concept consistent with the principles of the invention. As illustrated in Fig. 1, two distinct sets of data are used to detennine a score of a blog (or blog post) in response to a search query - the topical relevance of the blog (or blog post) to the terms in the search query and the quality of the blog (or blog post), which is independent of the query terms. The quality of the blog (or blog post) may positively or negatively affect the score of the blog (or blog post).
The plirase "blog document," as used hereinafter, is to be broadly interpreted to include a blog, a blog post, or both a blog and a blog post. It will be appreciated that the techniques described herein are equally applicable to blogs and blog posts. A"document," as the term is used herein, is to be broadly interpreted to include any machine-readable and machine-storable work product. A document may include, for exainple, an e-mail, a web site, a file, a coinbination of files, one or more files witli embedded links to other files, a news group posting, a blog docutnent, a web advertisement, etc. In the context of the Internet, a coinmon docuinent is a web
FIELD OF THE INVENTION
Implementations consistent with the principles of the invention relate generally to information retrieval and, more particularly, to providing a ranked set of blog documents in response to search queries.
BACKGROUND OF THE INVENTION
The World Wide Web ("web") contains a vast amount of information. Locating a desired portion of the information, however, can be challenging. This problem is compounded because the amount of information on the web and the number of new users inexperienced at web searching are growing rapidly.
Search engines attempt to return hyperlinks to web pages in which a user is interested. Generally, search engines base their detennination of the user's interest on search terms (called a search query) entered by the user. The goal of the search engine is to provide links to high quality, relevant results (e.g., web pages) to the user based on the search query. Typically, the search engine accomplishes this by matching the terms hi the search query to a corpus of pre-stored web pages. Web pages that contain the user's search terms are identified as search results and are returned to the user as links.
Over the past few years, a new medium, called a blog, has appeared on the web.
Blogs (short for web logs) are publications of personal thoughts that are typically updated frequently with new journal entries, called posts. The content and quality of blogs and their posts can vary greatly depending on the purpose of the authors of the blogs. As blogging becomes more popular, the ability to provide quality blog search results becomes more important.
SUMMARY OF THE INVENTION
In accordance with one iinplementation consistent with the principles of the invention, a method may include receiving a search queiy at a blog search engnie, retrieving a blog document in response to the search query, determining a first score for the blog docunlent based on the relevance of the blog document to the search query, altering the first score based on a quality of the blog docuinent, and providing infonnation regarding the blog document based on the altered first score.
In anotlier iunplementation consistent with the principles of the invention, a computer-implemented method includes obtaining a blog document, identifying at least one of the positive indicators of a quality of the blog document or negative indicators of the quality of the blog document, and determining a quality score for the blog document based on the identified at least one of positive indicators or negative indicators.
In yet another implementation consistent with the principles of the invention, a method may include receiving a search query at a blog search engine; determining scores for a group of blog documents in response to the search query, the scores being based on a relevance of the group of blog documents to the search query and a quality of the group of blog docmnents; and providing information regarding the group of blog documents based on the determined scores.
In still another iunplementation consistent with the principles of the invention, a method may include identifying at least one of the positive indicators of a quality of a blog docuinent or negative indicators of the quality of the blog document, the identified at least one of positive indicators or negative indicators including an indicator specific to blog documents; determining a quality score for the blog document based on the identified at least one of positive indicators or negative indicators; receiving a search query; determining a score for the blog document based on a relevance of the blog document to the search query;
adjusting the score of the blog document based on the quality score; and providing information relating to the blog document based on the adjusted score.
BRIEF DESCRIPTION OF THE DRAWINGS
The accompanyhig drawings, which are incorporated in and constitute a part of this specification, illustrate an innplementation of the invention and, together with the description, explain the invention. In the drawings, Fig. I is an exeinplary diagram illustrating a concept consistent with the principles of the invention;
Fig. 2 is an exemplary diagram of a networlc in wliich systems and methods consistent with the principles of the invention inay be implemented;
Fig. 3 is an exeinplary diagrani of a client or server entity in an implementation consistent with the principles of the invention;
Fig. 4 is a diagram of a portion of an exemplaiy computer-readable medium that may be used by the server of Fig. 2;
Fig. 5 is an exeinplary database that may be associated with the server of Fig. 2 in an implementation consistent with the principles of the invention;
Fig. 6 is a flow chart of an exemplary process for determining a quality score for a blog document in an implementation consistent with the principles of the invention;
Fig. 7 is a flowchart of an exemplary process for presenting search results in an implementation consistent witli the principles of the invention; and Fig. 8 is a diagram of an exeinplary set of documents that may be retrieved in an unplementation consistent with the principles of the invention.
DETAILED DESCRIPTION
The following detailed description of implementations consistent with the principles of the invention refers to the accompanying drawings. The same reference numbers in different drawings may identify the same or similar elements. Also, the following detailed description does not limit the invention.
OVERVIEW
Systems and methods consistent with the principles of the invention improve the quality of blog results provided in response to a search query. To iunprove the quality of blog results, a number of quality factors may be used to alter (either positively or negatively) a score of the blog results.
Fig. 1 is an exemplary diagrain illustrating a concept consistent with the principles of the invention. As illustrated in Fig. 1, two distinct sets of data are used to detennine a score of a blog (or blog post) in response to a search query - the topical relevance of the blog (or blog post) to the terms in the search query and the quality of the blog (or blog post), which is independent of the query terms. The quality of the blog (or blog post) may positively or negatively affect the score of the blog (or blog post).
The plirase "blog document," as used hereinafter, is to be broadly interpreted to include a blog, a blog post, or both a blog and a blog post. It will be appreciated that the techniques described herein are equally applicable to blogs and blog posts. A"document," as the term is used herein, is to be broadly interpreted to include any machine-readable and machine-storable work product. A document may include, for exainple, an e-mail, a web site, a file, a coinbination of files, one or more files witli embedded links to other files, a news group posting, a blog docutnent, a web advertisement, etc. In the context of the Internet, a coinmon docuinent is a web
3 page. Web pages often include textual information and may include einbedded information (such as meta infonnation, nnages, hyperlinlcs, etc.) and/or embedded instructions (such as Javascript, etc.). A"linlc," as the term is used herein, is to be broadly interpreted to include any reference to/from a document from/to another document or another part of the same document.
EXEMPLARY NETWORK CONFIGURATION
Fig. 2 is an exeinplary diagram of a network 200 in which systeins and methods consistent with the principles of the invention may be implemented. Network 200 may include multiple clients 210 connected to multiple servers 220-240 via a network 250. Two clients 210 and three servers 220-240 have been illustrated as connected to network 250 for simplicity. In practice, there may be more or fewer clients and servers. Also, in some instances, a client may perform a function of a server and a server may perform a function of a client.
Clients 210 may include client entities. An entity may be defined as a device, such as a personal computer, a wireless telephone, a personal digital assistant (PDA), a lap top, or another type of computation or coimnunication device, a thread or process running on one of these devices, and/or an object executable by one of these devices. Servers 220-240 may include server entities that gather, process, search, and/or maintain docuinents in a manner consistent with the principles of the invention.
In an implementation consistent with the principles of the invention, server 220 may include a search engine 225 usable by clients 210. In one implementation, search engine 225 may include a blog search engine that searches only blog documents. Server 220 may crawl a cozpus of documents, index the documents, and store information associated with tlie documents in a repository of documents.
Servers 230 and 240 may store or maintain documents that may be crawled or analyzed by server 220.
While servers 220-240 are shown as separate entities, it may be possible for one or more of servers 220-240 to perform one or more of the functions of anotlier one or more of servers 220-240. For example, it may be possible that two or more of servers 220-240 are implemented as a single server. It may also be possible for a single one of servers 220-240 to be implemented as two or more separate (and possibly distributed) devices.
Network 250 may uiclude a local area networlc (LAN), a wide area network (WAN), a telephone network, such as the Public Switched Telephone Networlc (PSTN), an intranet, the Internet, or a combination of
EXEMPLARY NETWORK CONFIGURATION
Fig. 2 is an exeinplary diagram of a network 200 in which systeins and methods consistent with the principles of the invention may be implemented. Network 200 may include multiple clients 210 connected to multiple servers 220-240 via a network 250. Two clients 210 and three servers 220-240 have been illustrated as connected to network 250 for simplicity. In practice, there may be more or fewer clients and servers. Also, in some instances, a client may perform a function of a server and a server may perform a function of a client.
Clients 210 may include client entities. An entity may be defined as a device, such as a personal computer, a wireless telephone, a personal digital assistant (PDA), a lap top, or another type of computation or coimnunication device, a thread or process running on one of these devices, and/or an object executable by one of these devices. Servers 220-240 may include server entities that gather, process, search, and/or maintain docuinents in a manner consistent with the principles of the invention.
In an implementation consistent with the principles of the invention, server 220 may include a search engine 225 usable by clients 210. In one implementation, search engine 225 may include a blog search engine that searches only blog documents. Server 220 may crawl a cozpus of documents, index the documents, and store information associated with tlie documents in a repository of documents.
Servers 230 and 240 may store or maintain documents that may be crawled or analyzed by server 220.
While servers 220-240 are shown as separate entities, it may be possible for one or more of servers 220-240 to perform one or more of the functions of anotlier one or more of servers 220-240. For example, it may be possible that two or more of servers 220-240 are implemented as a single server. It may also be possible for a single one of servers 220-240 to be implemented as two or more separate (and possibly distributed) devices.
Network 250 may uiclude a local area networlc (LAN), a wide area network (WAN), a telephone network, such as the Public Switched Telephone Networlc (PSTN), an intranet, the Internet, or a combination of
4 networlcs. Clients 210 and servers 220-240 may connect to networlc 250 via wired, wireless, and/or optical connections.
EXEMPLARY CLIENT/SERVER ARCHITECTURE
Fig. 3 is an exemplary diagram of a client or server entity (hereinafter called "client/server entity"), which may correspond to one or more of clients 210 and/or servers 220-240. The client/server entity may include a bus 310, a processor 320, a main memory 330, a read only memory (ROM) 340, a storage device 350, an input device 360, an output device 370, and a communication interface 380.
Bus 310 may include a path that permits communication among the elements of the client/server entity.
Processor 320 may include a processor, microprocessor, or processing logic that may interpret and execute instructions. Main meinory 330 may include a random access memoiy (RAM) or another type of dynainic storage device that may store information and instructions for execution by processor 320. ROM 340 may include a ROM device or another type of static storage device that may store static information and instructions for use by processor 320. Storage device 350 may include a magnetic and/or optical recording medium and its corresponding drive.
Input device 360 may include a mechanism that permits an operator to input information to the client/server entity, such as a keyboard, a mouse, a pen, voice recognition and/or biometric mechanisms, etc.
Output device 370 may include a mechanism that outputs information to the operator, includ'uig a display, a printer, a speaker, etc. Communication interface 380 may include any transceiver-like mechanism that enables the client/server entity to communicate with other devices and/or systems. For exainple, communication interface 380 may include mechanisms for communicating with another device or system via a networlc, such as networlc 250.
As will be described in detail below, the client/server entity, consistent with the principles of the invention, may perform certain docuinent processing-related operations. The client/server entity may perfoim these operations in response to processor 320 executing software instructions contained in a computer-readable medium, such as memoiy 330. A computer-readable medium may be defmed as a physical or logical memoiy device and/or carrier wave.
EXEMPLARY CLIENT/SERVER ARCHITECTURE
Fig. 3 is an exemplary diagram of a client or server entity (hereinafter called "client/server entity"), which may correspond to one or more of clients 210 and/or servers 220-240. The client/server entity may include a bus 310, a processor 320, a main memory 330, a read only memory (ROM) 340, a storage device 350, an input device 360, an output device 370, and a communication interface 380.
Bus 310 may include a path that permits communication among the elements of the client/server entity.
Processor 320 may include a processor, microprocessor, or processing logic that may interpret and execute instructions. Main meinory 330 may include a random access memoiy (RAM) or another type of dynainic storage device that may store information and instructions for execution by processor 320. ROM 340 may include a ROM device or another type of static storage device that may store static information and instructions for use by processor 320. Storage device 350 may include a magnetic and/or optical recording medium and its corresponding drive.
Input device 360 may include a mechanism that permits an operator to input information to the client/server entity, such as a keyboard, a mouse, a pen, voice recognition and/or biometric mechanisms, etc.
Output device 370 may include a mechanism that outputs information to the operator, includ'uig a display, a printer, a speaker, etc. Communication interface 380 may include any transceiver-like mechanism that enables the client/server entity to communicate with other devices and/or systems. For exainple, communication interface 380 may include mechanisms for communicating with another device or system via a networlc, such as networlc 250.
As will be described in detail below, the client/server entity, consistent with the principles of the invention, may perform certain docuinent processing-related operations. The client/server entity may perfoim these operations in response to processor 320 executing software instructions contained in a computer-readable medium, such as memoiy 330. A computer-readable medium may be defmed as a physical or logical memoiy device and/or carrier wave.
5 The software instructions may be read into memory 330 from another computer-readable medium, such as data storage device 350, or from another device via coinmunication interface 380. The software instructions contained in memory 330 may cause processor 320 to perform processes that will be described later.
Alternatively, hardwired circuitry may be used in place of or in combination with software instructions to impleinent processes consistent with the principles of the invention. Thus, implementations consistent with the principles of the invention are not lhnited to any specific coinbination of hardware circuitry and software.
EXEMPLARY COMPUTER-READABLE MEDIUM
Fig. 4 is a diagram of a portion of an exemplary coinputer-readable medium 400 that may be used by a server 220. In one implementation, computer-readable mediuin 400 may correspond to memory 330 of server 220. The portion of computer-readable medium 400 illustrated in Fig. 4 may include an operating system 410 and blog quality software 420.
Operating system 410 may include operating system software, such as the Windows, Unix, or Linux operating systems. Blog quality software 420 may include soflware that receives data relating to a blog document and deteimines, based on this data, a quality score for the blog document. As will be described in additional detail below, the data may include signals that measure the probability of the content of the blog document being of poor quality, which would lead to the demotion or elimination of the blog document as a candidate result. The data may also include signals that measure the probability of the content of the blog document being of higli quality/popularity, wliich would lead to the promotion of the blog docuinent as a candidate result.
Fig. 5 is an exemplary database 500 that may be associated with server 220 in an implementation consistent with the principles of the invention. Database 500 may be stored locally at server 220, for example, in main memory 330 or storage device 350, or stored external to server 220 at, for exaniple, a possibly remote location. As illustrated, database 500 may include the following exemplary fields: a document identification (ID) field 510 and a quality score field 520. It will be appreciated that database 500 may include otlier fields than those illustrated in Fig. 5.
Document ID field 510 may store information identifying blog documents, which, as described above, can be blogs or blog posts. The nnformation may include a unique identifier.
Quality score field 520 may store a
Alternatively, hardwired circuitry may be used in place of or in combination with software instructions to impleinent processes consistent with the principles of the invention. Thus, implementations consistent with the principles of the invention are not lhnited to any specific coinbination of hardware circuitry and software.
EXEMPLARY COMPUTER-READABLE MEDIUM
Fig. 4 is a diagram of a portion of an exemplary coinputer-readable medium 400 that may be used by a server 220. In one implementation, computer-readable mediuin 400 may correspond to memory 330 of server 220. The portion of computer-readable medium 400 illustrated in Fig. 4 may include an operating system 410 and blog quality software 420.
Operating system 410 may include operating system software, such as the Windows, Unix, or Linux operating systems. Blog quality software 420 may include soflware that receives data relating to a blog document and deteimines, based on this data, a quality score for the blog document. As will be described in additional detail below, the data may include signals that measure the probability of the content of the blog document being of poor quality, which would lead to the demotion or elimination of the blog document as a candidate result. The data may also include signals that measure the probability of the content of the blog document being of higli quality/popularity, wliich would lead to the promotion of the blog docuinent as a candidate result.
Fig. 5 is an exemplary database 500 that may be associated with server 220 in an implementation consistent with the principles of the invention. Database 500 may be stored locally at server 220, for example, in main memory 330 or storage device 350, or stored external to server 220 at, for exaniple, a possibly remote location. As illustrated, database 500 may include the following exemplary fields: a document identification (ID) field 510 and a quality score field 520. It will be appreciated that database 500 may include otlier fields than those illustrated in Fig. 5.
Document ID field 510 may store information identifying blog documents, which, as described above, can be blogs or blog posts. The nnformation may include a unique identifier.
Quality score field 520 may store a
6 quality score for each blog document identified in field 510. Database 500 may be accessed in response to a search query received by server 220. Server 220 may promote, demote, or even eliminate a blog docuwnent (i.e., blog and/or post) from a set of search results based on the quality score from field 520.
DETERMINING A QUALITY SCORE FOR A BLOG DOCUMENT
Fig. 6 is a flow chart of an exemplary process for determining a quality score for a blog document in an implementation consistent with the principles of the invention. Processing may begin by obtaining information regarding a blog document to be scored (act 610). The information may include the blog itself, the post, metadata from the blog, and/or one or more feeds associated with the blog docuinent.
Positive indicators as to the quality of the blog document may be identified (act 620). Such indicators may include a popularity of the blog document, an implied popularity of the blog document, the existence of the blog document in blogrolls, the existence of the blog document in a high quality blogroll, tagging of the blog document, references to the blog document by other sources, and a pageranlc of the blog docuinent. It will be appreciated that other indicators may also be used.
The popularity of the blog document may be a positive indication of the quality of that blog document.
A number of news aggregator sites (commonly called "news readers" or "feed readers") exist where individuals can subscribe to a blog docuinent (through its feed). Such aggregators store information describing how many individuals have subscribed to given blog docuinents. A blog document having a high number of subscriptions innplies a higher quality for the blog document. Also, subscriptions can be validated against "subscriptions spam" (where spammers subscribe to their own blog documents in an atteinpt to make them "more popular") by validating unique users who subscribed, or by filtering unique Internet Protocol (IP) addresses of the subscribers.
An unplied popularity may be identified for the blog document. This unplied popularity may be identified by, for example, examining the click stream of search results. For example, if a certain blog document is clicked more than other blog documents when the blog document appears in result sets, this may be an indication that the blog document is popular and, thus, a positive indicator of the quality of the blog document.
The existence of the blog document in blogrolls may be a positive indication of the quality of the blog document. It will be appreciated that blog documents often contain not only recent entries (i.e., posts), but also
DETERMINING A QUALITY SCORE FOR A BLOG DOCUMENT
Fig. 6 is a flow chart of an exemplary process for determining a quality score for a blog document in an implementation consistent with the principles of the invention. Processing may begin by obtaining information regarding a blog document to be scored (act 610). The information may include the blog itself, the post, metadata from the blog, and/or one or more feeds associated with the blog docuinent.
Positive indicators as to the quality of the blog document may be identified (act 620). Such indicators may include a popularity of the blog document, an implied popularity of the blog document, the existence of the blog document in blogrolls, the existence of the blog document in a high quality blogroll, tagging of the blog document, references to the blog document by other sources, and a pageranlc of the blog docuinent. It will be appreciated that other indicators may also be used.
The popularity of the blog document may be a positive indication of the quality of that blog document.
A number of news aggregator sites (commonly called "news readers" or "feed readers") exist where individuals can subscribe to a blog docuinent (through its feed). Such aggregators store information describing how many individuals have subscribed to given blog docuinents. A blog document having a high number of subscriptions innplies a higher quality for the blog document. Also, subscriptions can be validated against "subscriptions spam" (where spammers subscribe to their own blog documents in an atteinpt to make them "more popular") by validating unique users who subscribed, or by filtering unique Internet Protocol (IP) addresses of the subscribers.
An unplied popularity may be identified for the blog document. This unplied popularity may be identified by, for example, examining the click stream of search results. For example, if a certain blog document is clicked more than other blog documents when the blog document appears in result sets, this may be an indication that the blog document is popular and, thus, a positive indicator of the quality of the blog document.
The existence of the blog document in blogrolls may be a positive indication of the quality of the blog document. It will be appreciated that blog documents often contain not only recent entries (i.e., posts), but also
7 "blogrolls," which are a dense collection of links to external sites (usually other blogs) in which the author/blogger is interested. A blogroll link to a blog document is an indication of popularity of that blog document, so aggregated blogroll links to a blog document can be counted and used to infer magnitude of popularity for the blog document.
The existence of the blog document in a high quality blogroll may be a positive indication of the quality of the blog document. A high quality blogroll is a blogroll that links to well-known or trusted bloggers.
Therefore, a high quality blogroll that also linlcs to the blog document is a positive indicator of the quality of the blog document.
Shnlarly, the existence of the blog document in a blogroll of a well-lmown or trusted blogger may also be a positive indication of the quality of the blog document. In this situation, it is assumed that the well-known or trusted blogger would not linlc to' a spaimning blogger.
Tagging of the blog document may be a positive indication of the quality of the blog docuinent. Some existing sites allow users to add "tags" to (i.e., to "categorize") a blog document. These custom categorizations are an indicator that an individual has evaluated the content of the blog document and determined that one or more categories appropriately describe its content, and as such are a positive indicator of the quality of the blog document.
References to the blog document by other sources may be a positive indication of the quality of the blog dbcument. For example, content of emails or cliat transcripts can contain URLs of blog documents. Email or chat discussions that include references to the blog document is a positive indicator of the quality of the blog document.
The pageranlc of the blog document may be a positive uidicator of the quality of the blog document. A
high pagerank (a signal usually calculated for regular web pages) is an indicator of high quality and, thus, can be applied to blog documents as a positive indication of the quality of the blog documents. In some implementations, a blog document (e.g., a post) may not be associated with a pagerank (e.g., when the post is new). In those situations, the new post may inlierit the pagerank of the blog witll which it is associated until such time that an independent pageranlc is determined for the new post. This inlierited pagerank may serve as a positive indication of the quality of the new post.
The existence of the blog document in a high quality blogroll may be a positive indication of the quality of the blog document. A high quality blogroll is a blogroll that links to well-known or trusted bloggers.
Therefore, a high quality blogroll that also linlcs to the blog document is a positive indicator of the quality of the blog document.
Shnlarly, the existence of the blog document in a blogroll of a well-lmown or trusted blogger may also be a positive indication of the quality of the blog document. In this situation, it is assumed that the well-known or trusted blogger would not linlc to' a spaimning blogger.
Tagging of the blog document may be a positive indication of the quality of the blog docuinent. Some existing sites allow users to add "tags" to (i.e., to "categorize") a blog document. These custom categorizations are an indicator that an individual has evaluated the content of the blog document and determined that one or more categories appropriately describe its content, and as such are a positive indicator of the quality of the blog document.
References to the blog document by other sources may be a positive indication of the quality of the blog dbcument. For example, content of emails or cliat transcripts can contain URLs of blog documents. Email or chat discussions that include references to the blog document is a positive indicator of the quality of the blog document.
The pageranlc of the blog document may be a positive uidicator of the quality of the blog document. A
high pagerank (a signal usually calculated for regular web pages) is an indicator of high quality and, thus, can be applied to blog documents as a positive indication of the quality of the blog documents. In some implementations, a blog document (e.g., a post) may not be associated with a pagerank (e.g., when the post is new). In those situations, the new post may inlierit the pagerank of the blog witll which it is associated until such time that an independent pageranlc is determined for the new post. This inlierited pagerank may serve as a positive indication of the quality of the new post.
8 Negative indicators as to the quality of the blog document may be identified (act 630). Such indicators may include a frequency of new posts on the blog docuinent, the content of the posts in the blog document, a size of the posts in the blog document, a link distribution of the blog document, and the presence of ads in the blog document. It will be appreciated that other indicators may also be used.
The frequency at which new posts are added to the blog docuinent may be a negative indication of the quality of that blog document. Feeds typically include only the most recent posts from a blog document.
Spammers often generate new posts in spurts (i.e., many new posts appear within a short time period) or at predictable intervals (one post every 10 minutes, or a post every 3 hours at 32 minutes past the hour). Both behaviors are correlated with malicious intent and can be used to identify possible spaimners. Therefore, if the frequency at which new posts are added to the blog docuinent matches a predictable pattern, this may be a negative indication of the quality of the blog document.
The content of the posts in the blog document may be a negative indication of the quality of that blog document. A feed typically contains some or all of the content of several posts from a given blog document.
The blog document itself also includes the content of the posts. Spainmers may put one version of content into a feed to improve their ranlcing in search results, wliile putting a different version on their blog document (e.g., links to irrelevant ads). This mismatch (between feed and blog docmnent) can, therefore, be a negative indication of the quality of the blog document.
Also, in some instances, particular content may be duplicated in inultiple posts in a blog document, resulting in inultiple feeds containing the same content. Such duplication indicates the feed is low quality/spam and, thus, can be a negative indication of the quality of the blog docuinent.
The words/phrases used 'ni the posts of a blog docuinent may also be a negative indication of the quality of that blog document. For example, from a collection of blog documents and feeds that evaluators rate as spam, a list of words and phrases (bigrams, trigrams, etc.) that appear frequently in spam may be extracted. If a blog document contains a high percentage of words or phrases from the list, this can be a negative indication of quality of the blog document.
The size of the posts in a blog document may be a negative indication of quality of the blog document.
Many automated post generators create numerous posts of identical or veiy similar length. As a result, the
The frequency at which new posts are added to the blog docuinent may be a negative indication of the quality of that blog document. Feeds typically include only the most recent posts from a blog document.
Spammers often generate new posts in spurts (i.e., many new posts appear within a short time period) or at predictable intervals (one post every 10 minutes, or a post every 3 hours at 32 minutes past the hour). Both behaviors are correlated with malicious intent and can be used to identify possible spaimners. Therefore, if the frequency at which new posts are added to the blog docuinent matches a predictable pattern, this may be a negative indication of the quality of the blog document.
The content of the posts in the blog document may be a negative indication of the quality of that blog document. A feed typically contains some or all of the content of several posts from a given blog document.
The blog document itself also includes the content of the posts. Spainmers may put one version of content into a feed to improve their ranlcing in search results, wliile putting a different version on their blog document (e.g., links to irrelevant ads). This mismatch (between feed and blog docmnent) can, therefore, be a negative indication of the quality of the blog document.
Also, in some instances, particular content may be duplicated in inultiple posts in a blog document, resulting in inultiple feeds containing the same content. Such duplication indicates the feed is low quality/spam and, thus, can be a negative indication of the quality of the blog docuinent.
The words/phrases used 'ni the posts of a blog docuinent may also be a negative indication of the quality of that blog document. For example, from a collection of blog documents and feeds that evaluators rate as spam, a list of words and phrases (bigrams, trigrams, etc.) that appear frequently in spam may be extracted. If a blog document contains a high percentage of words or phrases from the list, this can be a negative indication of quality of the blog document.
The size of the posts in a blog document may be a negative indication of quality of the blog document.
Many automated post generators create numerous posts of identical or veiy similar length. As a result, the
9 distribution of post sizes can be used as a reliable measure of spamininess.
When a blog document includes numerous posts of identical or very similar length, this may be a negative indication of quality of the blog document.
A link distribution of the blog document may be a negative indication of quality of the blog docuinent.
As disclosed above, some posts are created to increase the pagerank of a particular blog document. In some cases, a high percentage of all links froin the posts or from the blog document all point to ether a single web page, or to a single external site. If the number of linlcs to any single external site exceeds a threshold, this can be a negative indication of quality of the blog document.
The presence of ads in the blog document may be a negative indication of quality of the blog docuinent.
If a blog document contains a large nuinber of ads, this may be a negative indication of the quality of the blog document.
Moreover, blog documents typically contain three types of content: the content of recent posts, a blogroll, and blog metadata (e.g., author profile information and/or other information pertinent to the blog document or its author). Ads, if present, typically appear within the blog inetadata section or near the blogroll.
The presence of ads in the recent posts part of a blog document inay be a negative indication of the quality of the blog document.
A quality score for the blog document may be determined based on these indicators (act 640). For example, in one implementation, the quality score for a blog docutnent may be determined by assigning a weight to the different indicators and combining the weights to obtain a quality score. The indicators may be coinbined andlor weighted in any manner. For example, in one implementation consistent with the principles of the invention, each indicator may be given a positive or negative value. These values may be added together to deterinine a quality score for the blog document. Alternatively, each indicator value may be multiplied by a corresponding factor (or weiglit) and the resulting values may be totaled to give the quality score for the blog document. Other techniques for determining the quality score may alternatively be used.
Once the quality score for the blog docuinent has been determined, it may be associated witll the blog document. For example, the quality score may be associated, in a database, such as database 500, with information identifying the blog document for which the score has been determined. In this manner, database 500 may be populated with quality scores for blog documents. The quality scores can be updated periodically.
PRESENTING SEARCH RESULTS
Fig. 7 is a flowchart of an exemplaiy process for presenting search results.
In one unplementation, the processing of Fig. 7 may be perfoi-med by one or more software and/or hardware components within server 220.
In another iunplementation, the processing may be performed by one or more software and/or hardware components within another device or a group of devices separate from or including server 220.
Processing may begin with a search query being received (act 710). For example, the user may provide a search query into a search box associated with a search engine (e.g., entering a search term into a search engine interface or a search box of an add-on toolbar). The web browser (or the add-on toolbar) may send the search query to a search engine, such as search engine 225 associated with server 220.
A relevance score for a set of documents may be determined based on the search query (act 720). For example, server 220 may determine an information retrieval (IR) score for the documents. The IR score for a document may be determined based on a matching of the search tenns of a search query to the content of the document. There are a nuinber of lcnown techniques that may be used to detennine the IR score for a docuinent.
For example, the IR score may be determined based on the number of occurrences of the search terms in the document. Alternatively or additionally, the IR score may be determined based on where the search terms occur within the document (e.g., title, content, etc.) or characteristics of the search terms (e.g., font, size, color, etc.).
Alternatively or additionally, a search tenn may be weighted differently from another search term when multiple search terms are present. Alternatively or additionally, the proximity of the search terins when inultiple search terms are present may influence the IR score. Yet other techniques for deterinining the IR score for a docmnent are known to those skilled in the art.
An overall score for the documents may be deterinined based on the quality of the docuinents (act 730).
For example, the IR score for each document may be combined with the document's quality score to deterinine the overall score. Coinbining the scores may cause the IR scores for the documents to be adjusted based on the quality scores, thereby raising or lowering the scores or, in some cases, leaving the scores the same to obtain the overall scores. Alternatively, the docuinents may be scored based on the quality scores alone without generating IR scores. Tn any event, overall scores may be determined for the documents using the quality scores.
A ranlced set of documents may be provided to the user based on the overall scores for the docuinents (act 740). In this way, the quality of documents may be used to iunprove the search results provided to users.
EXAMPLE
The following exainple illustrates the above processing. Assuine that a user is interested in blogs about fantasy football. The user may submit the search query "fantasy football" to a search engine, such as search engine 225. In response, assume that search engine 225 retrieves a group of blog documents based on their relevance to the search query (e.g., using an IR technique).
Fig. 8 is a diagrain of an exemplary set of blog documents received in response to the search query. As illustrated, search engine 225 retrieved five blog documents (blog docuinents 1-5) with the following relevance (or IR) scores: blog document 1 has an IR score of 1.0, blog document 2 has an IR score of 0.9, blog docunient 3 has an IR score of 0,8, blog document 4 has an IR score of 0.7, and blog document 5 has an IR score of 0.6.
Assuine, for explanatory purposes, that these five blog documents have the following quality scores: blog document 1 has a positive quality score of 0.4, blog document 2 has a negative quality score of -0.4, blog document 3 has apositive quality score of 0.8, blog document 4 has a positive quality score of 0.3, and blog document 5 has a positive quality score of 0.3.
Search engine 225 may detennine an overall score for the blog documents by adding the relevance score to the quality score. In this case, blog document 1 would have an overall score of 1.4, blog document 2 would have an overall score of 0.5, blog docuinent 3 would have an overall score of 1.6, blog document 4 would have an overall score of 1.0, and blog docunient 5 would have an overall score of 0.9. Therefore, search engine 225 may provide blog documents 1-5 to the user in the following order: blog document 3, blog docuinent 1, blog document 4, blog document 5, and blog document 2.
As evident fi=om the example of Fig. 8, the quality of blog documents may cause the ranlcing of those documents to increase or decrease. In this way, higher quality results are provided to the user.
CONCLUSION
Iinplementations consistent witli the principles of the invention iinprove blog searching by taking into consideration the quality of the blogs.
The foregoing description of exemplary embodiments of the invention provides illustration and description, but is not intended to be exhaustive or to limit the invention to the precise form disclosed.
Modifications and variations are possible in light of the above teachings or may be acquired from practice of the invention.
For example, while series of acts have been described with regard to Figs. 6 and 7, the order of the acts may be modified in other implementations consistent with the principles of the invention. Further, non-dependent acts may be performed in parallel.
The preceding description refers to a user. A"user" is intended to refer to a client, sucli as a client 210 (Fig. 2), or an operator of a client.
It will be apparent to one of ordinaiy skill in the art that aspects of the invention, as described above, may be implemented in many different fonns of software, firmware, and hardware in the implementations illustrated in the figures. The actual software code or specialized control hardware used to implement aspects consistent with the principles of the invention is not limiting of the invention. Thus, the operation and behavior of the aspects were described without reference to the specific software code--it being understood that one of ordinary slcill in the art would be able to design software and control hardware to' implement the aspects based on the description herein.
No element, act, or instruction used in the present application should be construed as critical or essential to the invention unless explicitly described as such. Also, as used herein, the article "a" is intended to include one or more items. Where only one item is intended, the term "one" or similar language is used.
Further, the phrase "based on" is intended to inean "based, at least in part, on" unless explicitly stated otherwise.
When a blog document includes numerous posts of identical or very similar length, this may be a negative indication of quality of the blog document.
A link distribution of the blog document may be a negative indication of quality of the blog docuinent.
As disclosed above, some posts are created to increase the pagerank of a particular blog document. In some cases, a high percentage of all links froin the posts or from the blog document all point to ether a single web page, or to a single external site. If the number of linlcs to any single external site exceeds a threshold, this can be a negative indication of quality of the blog document.
The presence of ads in the blog document may be a negative indication of quality of the blog docuinent.
If a blog document contains a large nuinber of ads, this may be a negative indication of the quality of the blog document.
Moreover, blog documents typically contain three types of content: the content of recent posts, a blogroll, and blog metadata (e.g., author profile information and/or other information pertinent to the blog document or its author). Ads, if present, typically appear within the blog inetadata section or near the blogroll.
The presence of ads in the recent posts part of a blog document inay be a negative indication of the quality of the blog document.
A quality score for the blog document may be determined based on these indicators (act 640). For example, in one implementation, the quality score for a blog docutnent may be determined by assigning a weight to the different indicators and combining the weights to obtain a quality score. The indicators may be coinbined andlor weighted in any manner. For example, in one implementation consistent with the principles of the invention, each indicator may be given a positive or negative value. These values may be added together to deterinine a quality score for the blog document. Alternatively, each indicator value may be multiplied by a corresponding factor (or weiglit) and the resulting values may be totaled to give the quality score for the blog document. Other techniques for determining the quality score may alternatively be used.
Once the quality score for the blog docuinent has been determined, it may be associated witll the blog document. For example, the quality score may be associated, in a database, such as database 500, with information identifying the blog document for which the score has been determined. In this manner, database 500 may be populated with quality scores for blog documents. The quality scores can be updated periodically.
PRESENTING SEARCH RESULTS
Fig. 7 is a flowchart of an exemplaiy process for presenting search results.
In one unplementation, the processing of Fig. 7 may be perfoi-med by one or more software and/or hardware components within server 220.
In another iunplementation, the processing may be performed by one or more software and/or hardware components within another device or a group of devices separate from or including server 220.
Processing may begin with a search query being received (act 710). For example, the user may provide a search query into a search box associated with a search engine (e.g., entering a search term into a search engine interface or a search box of an add-on toolbar). The web browser (or the add-on toolbar) may send the search query to a search engine, such as search engine 225 associated with server 220.
A relevance score for a set of documents may be determined based on the search query (act 720). For example, server 220 may determine an information retrieval (IR) score for the documents. The IR score for a document may be determined based on a matching of the search tenns of a search query to the content of the document. There are a nuinber of lcnown techniques that may be used to detennine the IR score for a docuinent.
For example, the IR score may be determined based on the number of occurrences of the search terms in the document. Alternatively or additionally, the IR score may be determined based on where the search terms occur within the document (e.g., title, content, etc.) or characteristics of the search terms (e.g., font, size, color, etc.).
Alternatively or additionally, a search tenn may be weighted differently from another search term when multiple search terms are present. Alternatively or additionally, the proximity of the search terins when inultiple search terms are present may influence the IR score. Yet other techniques for deterinining the IR score for a docmnent are known to those skilled in the art.
An overall score for the documents may be deterinined based on the quality of the docuinents (act 730).
For example, the IR score for each document may be combined with the document's quality score to deterinine the overall score. Coinbining the scores may cause the IR scores for the documents to be adjusted based on the quality scores, thereby raising or lowering the scores or, in some cases, leaving the scores the same to obtain the overall scores. Alternatively, the docuinents may be scored based on the quality scores alone without generating IR scores. Tn any event, overall scores may be determined for the documents using the quality scores.
A ranlced set of documents may be provided to the user based on the overall scores for the docuinents (act 740). In this way, the quality of documents may be used to iunprove the search results provided to users.
EXAMPLE
The following exainple illustrates the above processing. Assuine that a user is interested in blogs about fantasy football. The user may submit the search query "fantasy football" to a search engine, such as search engine 225. In response, assume that search engine 225 retrieves a group of blog documents based on their relevance to the search query (e.g., using an IR technique).
Fig. 8 is a diagrain of an exemplary set of blog documents received in response to the search query. As illustrated, search engine 225 retrieved five blog documents (blog docuinents 1-5) with the following relevance (or IR) scores: blog document 1 has an IR score of 1.0, blog document 2 has an IR score of 0.9, blog docunient 3 has an IR score of 0,8, blog document 4 has an IR score of 0.7, and blog document 5 has an IR score of 0.6.
Assuine, for explanatory purposes, that these five blog documents have the following quality scores: blog document 1 has a positive quality score of 0.4, blog document 2 has a negative quality score of -0.4, blog document 3 has apositive quality score of 0.8, blog document 4 has a positive quality score of 0.3, and blog document 5 has a positive quality score of 0.3.
Search engine 225 may detennine an overall score for the blog documents by adding the relevance score to the quality score. In this case, blog document 1 would have an overall score of 1.4, blog document 2 would have an overall score of 0.5, blog docuinent 3 would have an overall score of 1.6, blog document 4 would have an overall score of 1.0, and blog docunient 5 would have an overall score of 0.9. Therefore, search engine 225 may provide blog documents 1-5 to the user in the following order: blog document 3, blog docuinent 1, blog document 4, blog document 5, and blog document 2.
As evident fi=om the example of Fig. 8, the quality of blog documents may cause the ranlcing of those documents to increase or decrease. In this way, higher quality results are provided to the user.
CONCLUSION
Iinplementations consistent witli the principles of the invention iinprove blog searching by taking into consideration the quality of the blogs.
The foregoing description of exemplary embodiments of the invention provides illustration and description, but is not intended to be exhaustive or to limit the invention to the precise form disclosed.
Modifications and variations are possible in light of the above teachings or may be acquired from practice of the invention.
For example, while series of acts have been described with regard to Figs. 6 and 7, the order of the acts may be modified in other implementations consistent with the principles of the invention. Further, non-dependent acts may be performed in parallel.
The preceding description refers to a user. A"user" is intended to refer to a client, sucli as a client 210 (Fig. 2), or an operator of a client.
It will be apparent to one of ordinaiy skill in the art that aspects of the invention, as described above, may be implemented in many different fonns of software, firmware, and hardware in the implementations illustrated in the figures. The actual software code or specialized control hardware used to implement aspects consistent with the principles of the invention is not limiting of the invention. Thus, the operation and behavior of the aspects were described without reference to the specific software code--it being understood that one of ordinary slcill in the art would be able to design software and control hardware to' implement the aspects based on the description herein.
No element, act, or instruction used in the present application should be construed as critical or essential to the invention unless explicitly described as such. Also, as used herein, the article "a" is intended to include one or more items. Where only one item is intended, the term "one" or similar language is used.
Further, the phrase "based on" is intended to inean "based, at least in part, on" unless explicitly stated otherwise.
Claims (27)
1. A method comprising:
receiving a search query by a blog search engine;
retrieving a blog document in response to the search query;
determining a first score for the blog document based on the relevance of the blog document to the search query;
altering the first score based on a quality of the blog document; and providing information regarding the blog document based on the altered first score.
receiving a search query by a blog search engine;
retrieving a blog document in response to the search query;
determining a first score for the blog document based on the relevance of the blog document to the search query;
altering the first score based on a quality of the blog document; and providing information regarding the blog document based on the altered first score.
2. The method of claim 1 wherein the blog document includes a blog or a blog post.
3. The method of claim 1 further comprising:
determining the quality of the blog document based on a plurality of indicators.
determining the quality of the blog document based on a plurality of indicators.
4. The method of claim 3 wherein the plurality of indicators includes at least one of one or more positive indicators or one or more negative indicators.
5. The method of claim 4 wherein the one or more positive indicators include one or more of a popularity of the blog document, an existence of a link to the blog document in one or more blogrolls associated with other blog documents, tagging of the blog document, a reference to the blog document in other documents, or a pagerank of the blog document, and wherein the one or more negative indicators include one or more of a frequency with which posts are added to the blog document, a content of the blog document, a size of posts in the blog document, a link distribution associated with the blog document, a quantity of ads in the blog document, or a location of ads in the blog document.
6. The method of claim 4 wherein the determining the quality of the blog document includes:
combining the one or more positive indicators and the one or more negative indicators to determine a quality score for the blog document.
combining the one or more positive indicators and the one or more negative indicators to determine a quality score for the blog document.
7. The method of claim 6 wherein the altering the first score includes:
increasing or decreasing the first score based on the quality score.
increasing or decreasing the first score based on the quality score.
8. The method of claim 1 wherein the quality of the blog document is unrelated to the search query.
9. A system comprising:
means for receiving a search query by a blog search engine;
means for obtaining a blog document in response to the search query;
means for determining a first score for the blog document based on the relevance of the blog document to the search query;
means for adjusting the first score based on a quality of the blog document;
and means for providing information relating to the blog document based on the adjusted first score.
means for receiving a search query by a blog search engine;
means for obtaining a blog document in response to the search query;
means for determining a first score for the blog document based on the relevance of the blog document to the search query;
means for adjusting the first score based on a quality of the blog document;
and means for providing information relating to the blog document based on the adjusted first score.
10. A device coinprising:
a blog search engine to:
receive a search query;
retrieve a plurality of blog documents in response to the search query;
determine a first score for each blog document in the plurality of blog documents based on the relevance of the each blog document to the search query;
alter the first score of each blog document based on a quality of the each blog document; and provide information regarding the blog documents based on the altered first scores.
a blog search engine to:
receive a search query;
retrieve a plurality of blog documents in response to the search query;
determine a first score for each blog document in the plurality of blog documents based on the relevance of the each blog document to the search query;
alter the first score of each blog document based on a quality of the each blog document; and provide information regarding the blog documents based on the altered first scores.
11. A computer-readable medium containing instructions for controlling a processor to perform a method comprising:
receiving a search query by a blog search engine;
retrieving documents in response to the search query, the documents including a blog document;
determining scores for the documents based on the relevance of the documents to the search query;
altering the score of the blog document based on a quality of the blog document; and providing information regarding the documents based on the determined scores and altered score.
receiving a search query by a blog search engine;
retrieving documents in response to the search query, the documents including a blog document;
determining scores for the documents based on the relevance of the documents to the search query;
altering the score of the blog document based on a quality of the blog document; and providing information regarding the documents based on the determined scores and altered score.
12. A computer-implemented method coinprising:
obtaining a blog document;
identifying at least one of positive indictors of a quality of the blog document or negative indicators of the quality of the blog document; and determining a quality score for the blog document based on the identified at least one of positive indicators or negative indicators.
obtaining a blog document;
identifying at least one of positive indictors of a quality of the blog document or negative indicators of the quality of the blog document; and determining a quality score for the blog document based on the identified at least one of positive indicators or negative indicators.
13. The computer-implemented method of claim 12 wherein the blog document includes a blog or a blog post.
14. The computer-implemented method of claim 12 wherein the positive indicators include one or more of a popularity of the blog document, an existence of a link to the blog document in one or more blogrolls associated with other blog documents, a tagging of the blog document, a reference to the blog document in other documents, or a pagerank of the blog document.
15. The computer-implemented method of claim 12 wherein the negative indicators include one or more of a frequency with which posts are added to the blog document, a size of posts in the blog document, a link distribution associated with the blog document, a quantity of ads in the blog document, or a location of ads in the blog document.
16. The computer-implemented method of claim 12 wherein the negative indicators include an indication of a mismatch between a content of the blog document and a content of a feed associated with the blog document.
17. The computer-implemented method of claim 12 wherein the negative indicators include an indication that the blog document includes a high percentage of predetermined words or phrases.
18. The computer-implemented method of claim 12 wherein the negative indicators include an indication that the blog document includes duplicate content.
19. The computer-implemented method of claim 12 further comprising:
using the quality score in ranking the blog document in response to a search query.
using the quality score in ranking the blog document in response to a search query.
20. A device comprising:
logic to receive a blog document;
logic to identify at least one of positive indictors of a quality of the blog document or negative indicators of the quality of the blog document; and logic to determine a quality for the blog document based on the identified at least one of positive indicators or negative indicators.
logic to receive a blog document;
logic to identify at least one of positive indictors of a quality of the blog document or negative indicators of the quality of the blog document; and logic to determine a quality for the blog document based on the identified at least one of positive indicators or negative indicators.
21. A method comprising:
receiving a search query at a blog search engine;
determining scores for a plurality of blog documents in response to the search query, the scores being based on a relevance of the plurality of blog documents to the search query and a quality of the plurality of blog documents; and providing information regarding the plurality of blog documents based on the determined scores.
receiving a search query at a blog search engine;
determining scores for a plurality of blog documents in response to the search query, the scores being based on a relevance of the plurality of blog documents to the search query and a quality of the plurality of blog documents; and providing information regarding the plurality of blog documents based on the determined scores.
22. The method of claim 21 wherein the determining scores includes:
determining relevance scores for the plurality of blog documents, and adjusting the relevance scores based on the quality of the plurality of blog documents.
determining relevance scores for the plurality of blog documents, and adjusting the relevance scores based on the quality of the plurality of blog documents.
23. The method of claim 21 further comprising:
determining the quality of each blog document in the plurality of blog documents based on a plurality of indicators.
determining the quality of each blog document in the plurality of blog documents based on a plurality of indicators.
24. The method of claim 23 wherein the plurality of indicators includes one or more positive indicators and one or more negative indicators.
25. The method of claim 24 wherein the one or more positive indicators include one or more of a popularity of the blog document, an existence of a link to the blog document in one or more blogrolls associated with other blog documents, a tagging of the blog document, a reference to the blog document in other documents, or a pagerank of the blog document, and wherein the one or more negative indicators include one or more of a frequency with which posts are added to the blog document, a content of the blog document, a size of posts in the blog document, a link distribution associated with the blog document, a quantity of ads in the blog document, or a location of ads in the blog document.
26. The method of claim 24 wherein the determining the quality of each blog document includes:
combining the one or more positive indicators and the one or more negative indicators to determine a quality score for the each blog document.
combining the one or more positive indicators and the one or more negative indicators to determine a quality score for the each blog document.
27. A method comprising:
identifying at least one of positive indictors of a quality of a blog document or negative indicators of the quality of the blog document, the identified at least one of positive indicators or negative indicators including an indicator specific to blog documents;
determining a quality score for the blog document based on the identified at least one of positive indicators or negative indicators;
receiving a search query;
determining a score for the blog document based on a relevance of the blog document to the search query;
adjusting the score of the blog document based on the quality score; and providing information relating to the blog document based on the adjusted score.
identifying at least one of positive indictors of a quality of a blog document or negative indicators of the quality of the blog document, the identified at least one of positive indicators or negative indicators including an indicator specific to blog documents;
determining a quality score for the blog document based on the identified at least one of positive indicators or negative indicators;
receiving a search query;
determining a score for the blog document based on a relevance of the blog document to the search query;
adjusting the score of the blog document based on the quality score; and providing information relating to the blog document based on the adjusted score.
Applications Claiming Priority (3)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| US11/224,321 | 2005-09-13 | ||
| US11/224,321 US8244720B2 (en) | 2005-09-13 | 2005-09-13 | Ranking blog documents |
| PCT/US2006/035539 WO2007033202A1 (en) | 2005-09-13 | 2006-09-13 | Ranking blog documents |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CA2622784A1 true CA2622784A1 (en) | 2007-03-22 |
Family
ID=37432282
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CA002622784A Abandoned CA2622784A1 (en) | 2005-09-13 | 2006-09-13 | Ranking blog documents |
Country Status (9)
| Country | Link |
|---|---|
| US (2) | US8244720B2 (en) |
| EP (1) | EP1934830A1 (en) |
| JP (2) | JP4837040B2 (en) |
| KR (1) | KR101005510B1 (en) |
| CN (1) | CN101305371A (en) |
| AU (1) | AU2006290977B2 (en) |
| BR (1) | BRPI0615915B1 (en) |
| CA (1) | CA2622784A1 (en) |
| WO (1) | WO2007033202A1 (en) |
Families Citing this family (55)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7421429B2 (en) * | 2005-08-04 | 2008-09-02 | Microsoft Corporation | Generate blog context ranking using track-back weight, context weight and, cumulative comment weight |
| US8244720B2 (en) | 2005-09-13 | 2012-08-14 | Google Inc. | Ranking blog documents |
| US7856445B2 (en) * | 2005-11-30 | 2010-12-21 | John Nicholas and Kristin Gross | System and method of delivering RSS content based advertising |
| US8924558B2 (en) | 2005-11-30 | 2014-12-30 | John Nicholas and Kristin Gross | System and method of delivering content based advertising |
| US9202241B2 (en) * | 2005-11-30 | 2015-12-01 | John Nicholas and Kristin Gross | System and method of delivering content based advertising |
| US8417569B2 (en) | 2005-11-30 | 2013-04-09 | John Nicholas and Kristin Gross Trust | System and method of evaluating content based advertising |
| US8117195B1 (en) | 2006-03-22 | 2012-02-14 | Google Inc. | Providing blog posts relevant to search results |
| US20070239674A1 (en) * | 2006-04-11 | 2007-10-11 | Richard Gorzela | Method and System for Providing Weblog Author-Defined, Weblog-Specific Search Scopes in Weblogs |
| US20070255701A1 (en) * | 2006-04-28 | 2007-11-01 | Halla Jason M | System and method for analyzing internet content and correlating to events |
| US20090070683A1 (en) * | 2006-05-05 | 2009-03-12 | Miles Ward | Consumer-generated media influence and sentiment determination |
| US20070271259A1 (en) * | 2006-05-17 | 2007-11-22 | It Interactive Services Inc. | System and method for geographically focused crawling |
| US8452777B2 (en) * | 2007-02-01 | 2013-05-28 | Linkedin Corporation | Dynamic submission and preference indicator |
| US8527594B2 (en) * | 2007-02-16 | 2013-09-03 | Ecairn, Inc. | Blog advertising |
| US8346763B2 (en) * | 2007-03-30 | 2013-01-01 | Microsoft Corporation | Ranking method using hyperlinks in blogs |
| US20090006341A1 (en) * | 2007-06-28 | 2009-01-01 | Bruce Chapman | Method of website ranking promotion using creation of mass blog posting links |
| WO2009023984A1 (en) | 2007-08-17 | 2009-02-26 | Google Inc. | Ranking social network objects |
| CN100545847C (en) * | 2007-09-25 | 2009-09-30 | 腾讯科技（深圳）有限公司 | A kind of method and system that blog articles is sorted |
| KR100932841B1 (en) * | 2007-11-09 | 2009-12-21 | 엔에이치엔(주) | Search document quality measurement method and system |
| KR100932842B1 (en) * | 2007-12-06 | 2009-12-21 | 엔에이치엔(주) | Quality ranking method and system of search ranking |
| KR100975502B1 (en) * | 2008-01-30 | 2010-08-11 | 엔에이치엔(주) | System and Method for Determining Ranking of Blog Post |
| US8078197B2 (en) * | 2008-02-20 | 2011-12-13 | Agere Systems Inc. | Location-based search-result ranking for blog documents and the like |
| KR101004999B1 (en) * | 2008-08-27 | 2011-01-04 | 서강대학교산학협력단 | Method and device for measuring propagation of contents and site of offering the contents |
| US8082288B1 (en) * | 2008-10-17 | 2011-12-20 | GO Interactive, Inc. | Method and apparatus for determining notable content on web sites using collected comments |
| KR101013761B1 (en) * | 2008-10-27 | 2011-02-14 | 한국과학기술원 | Blog search apparatus and method using authority estimation in blog space |
| US20100114910A1 (en) * | 2008-10-27 | 2010-05-06 | Korea Advanced Institute Of Science And Technology | Blog search apparatus and method using blog authority estimation |
| KR101049648B1 (en) | 2009-02-23 | 2011-07-14 | 성균관대학교산학협력단 | Blog Rank Method for Efficiently Searching Blogs Using the Blog Rank Algorithm |
| JP5216654B2 (en) * | 2009-03-27 | 2013-06-19 | Ｋｄｄｉ株式会社 | Importance determination device, importance determination method, and program |
| US8577910B1 (en) | 2009-05-15 | 2013-11-05 | Google Inc. | Selecting relevant languages for query translation |
| US8577909B1 (en) | 2009-05-15 | 2013-11-05 | Google Inc. | Query translation using bilingual search refinements |
| US8572109B1 (en) | 2009-05-15 | 2013-10-29 | Google Inc. | Query translation quality confidence |
| US8538957B1 (en) * | 2009-06-03 | 2013-09-17 | Google Inc. | Validating translations using visual similarity between visual media search results |
| US8745067B2 (en) * | 2009-08-12 | 2014-06-03 | Google Inc. | Presenting comments from various sources |
| KR101284788B1 (en) * | 2009-10-13 | 2013-07-10 | 한국전자통신연구원 | Apparatus for question answering based on answer trustworthiness and method thereof |
| US8606792B1 (en) * | 2010-02-08 | 2013-12-10 | Google Inc. | Scoring authors of posts |
| US20110258560A1 (en) * | 2010-04-14 | 2011-10-20 | Microsoft Corporation | Automatic gathering and distribution of testimonial content |
| US20110276554A1 (en) * | 2010-05-10 | 2011-11-10 | Chen-Yu Sheu | Query and note based search system |
| US8560530B2 (en) | 2010-05-17 | 2013-10-15 | Buzzmetrics, Ltd. | Methods, apparatus, and articles of manufacture to rank web site influence |
| AU2013203650B2 (en) * | 2010-05-17 | 2014-08-14 | Buzzmetrics Ltd. | Methods, apparatus and articles of manufacture to rank web site influence |
| US8849807B2 (en) | 2010-05-25 | 2014-09-30 | Mark F. McLellan | Active search results page ranking technology |
| CN102385576A (en) * | 2010-08-27 | 2012-03-21 | 腾讯科技（深圳）有限公司 | Method and system for counting influence of Bloger |
| US9009065B2 (en) | 2010-12-17 | 2015-04-14 | Google Inc. | Promoting content from an activity stream |
| JP2012141837A (en) * | 2011-01-04 | 2012-07-26 | Sony Corp | Information processor, information processing method and program |
| US20120210240A1 (en) * | 2011-02-10 | 2012-08-16 | Microsoft Corporation | User interfaces for personalized recommendations |
| US9251269B2 (en) * | 2011-10-27 | 2016-02-02 | International Business Machines Corporation | Accounting for authorship in a web log search engine |
| US9135291B2 (en) * | 2011-12-14 | 2015-09-15 | Megathread, Ltd. | System and method for determining similarities between online entities |
| US9589303B2 (en) * | 2012-01-09 | 2017-03-07 | Google Inc. | Selective presentation of content types and sources in search |
| CN103246670B (en) * | 2012-02-09 | 2016-02-17 | 深圳市腾讯计算机系统有限公司 | Microblogging sequence, search, methods of exhibiting and system |
| JP5962213B2 (en) * | 2012-05-28 | 2016-08-03 | ソニー株式会社 | Information processing apparatus, information processing method, and program |
| KR101630136B1 (en) * | 2012-07-06 | 2016-06-13 | 엠파이어 테크놀로지 디벨롭먼트 엘엘씨 | Organization of inputs for online service |
| US9553783B2 (en) * | 2012-09-14 | 2017-01-24 | Salesforce.Com, Inc. | Spam flood detection methodologies |
| CN103914491B (en) * | 2013-01-09 | 2017-11-17 | 腾讯科技（北京）有限公司 | To the data digging method and system of high-quality user-generated content |
| JP6130270B2 (en) * | 2013-08-21 | 2017-05-17 | Kddi株式会社 | Comment list public server, program and method for sorting and specifying comment sets corresponding to media contents |
| US10303684B1 (en) * | 2013-08-27 | 2019-05-28 | Google Llc | Resource scoring adjustment based on entity selections |
| US9589024B2 (en) * | 2013-09-27 | 2017-03-07 | Intel Corporation | Mechanism for facilitating dynamic and proactive data management for computing devices |
| CN105488151A (en) * | 2015-11-27 | 2016-04-13 | 小米科技有限责任公司 | Reference document recommendation method and apparatus |
Family Cites Families (53)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6421675B1 (en) | 1998-03-16 | 2002-07-16 | S. L. I. Systems, Inc. | Search engine |
| US6598046B1 (en) * | 1998-09-29 | 2003-07-22 | Qwest Communications International Inc. | System and method for retrieving documents responsive to a given user's role and scenario |
| US6510406B1 (en) | 1999-03-23 | 2003-01-21 | Mathsoft, Inc. | Inverse inference engine for high performance web search |
| US7693830B2 (en) * | 2005-08-10 | 2010-04-06 | Google Inc. | Programmable search engine |
| US7716199B2 (en) * | 2005-08-10 | 2010-05-11 | Google Inc. | Aggregating context data for programmable search engines |
| US7743045B2 (en) * | 2005-08-10 | 2010-06-22 | Google Inc. | Detecting spam related and biased contexts for programmable search engines |
| US6946715B2 (en) * | 2003-02-19 | 2005-09-20 | Micron Technology, Inc. | CMOS image sensor and method of fabrication |
| US7016889B2 (en) * | 2003-01-30 | 2006-03-21 | Hewlett-Packard Development Company, Lp. | System and method for identifying useful content in a knowledge repository |
| US7739281B2 (en) * | 2003-09-16 | 2010-06-15 | Microsoft Corporation | Systems and methods for ranking documents based upon structurally interrelated information |
| US7346839B2 (en) | 2003-09-30 | 2008-03-18 | Google Inc. | Information retrieval based on historical data |
| KR20050077242A (en) | 2004-02-10 | 2005-08-01 | 엔에이치엔(주) | Method for offering an advertisement on search-result in response to the search-demand and a system thereof |
| US8930239B2 (en) * | 2005-03-23 | 2015-01-06 | Douglas Ashbaugh | Distributed content exchange and presentation system |
| US7761447B2 (en) * | 2004-04-08 | 2010-07-20 | Microsoft Corporation | Systems and methods that rank search results |
| US20070067297A1 (en) * | 2004-04-30 | 2007-03-22 | Kublickis Peter J | System and methods for a micropayment-enabled marketplace with permission-based, self-service, precision-targeted delivery of advertising, entertainment and informational content and relationship marketing to anonymous internet users |
| US7596571B2 (en) * | 2004-06-30 | 2009-09-29 | Technorati, Inc. | Ecosystem method of aggregation and search and related techniques |
| US7890871B2 (en) * | 2004-08-26 | 2011-02-15 | Redlands Technology, Llc | System and method for dynamically generating, maintaining, and growing an online social network |
| US8335785B2 (en) * | 2004-09-28 | 2012-12-18 | Hewlett-Packard Development Company, L.P. | Ranking results for network search query |
| US8060463B1 (en) * | 2005-03-30 | 2011-11-15 | Amazon Technologies, Inc. | Mining of user event data to identify users with common interests |
| WO2006128136A2 (en) * | 2005-05-25 | 2006-11-30 | Insider Pages | Structured blogging with reciprocal links |
| US9158855B2 (en) * | 2005-06-16 | 2015-10-13 | Buzzmetrics, Ltd | Extracting structured data from weblogs |
| US7421429B2 (en) * | 2005-08-04 | 2008-09-02 | Microsoft Corporation | Generate blog context ranking using track-back weight, context weight and, cumulative comment weight |
| US20070050389A1 (en) * | 2005-09-01 | 2007-03-01 | Opinmind, Inc. | Advertisement placement based on expressions about topics |
| US8244720B2 (en) | 2005-09-13 | 2012-08-14 | Google Inc. | Ranking blog documents |
| US7765209B1 (en) * | 2005-09-13 | 2010-07-27 | Google Inc. | Indexing and retrieval of blogs |
| US8688673B2 (en) * | 2005-09-27 | 2014-04-01 | Sarkar Pte Ltd | System for communication and collaboration |
| US7716226B2 (en) * | 2005-09-27 | 2010-05-11 | Patentratings, Llc | Method and system for probabilistically quantifying and visualizing relevance between two or more citationally or contextually related data objects |
| US7657585B2 (en) * | 2005-10-25 | 2010-02-02 | Innternational Business Machines Corporation | Automated process for identifying and delivering domain specific unstructured content for advanced business analysis |
| US7917519B2 (en) * | 2005-10-26 | 2011-03-29 | Sizatola, Llc | Categorized document bases |
| US20070255702A1 (en) * | 2005-11-29 | 2007-11-01 | Orme Gregory M | Search Engine |
| US7734610B2 (en) * | 2005-12-12 | 2010-06-08 | Google Inc. | Decentralised web annotation |
| US7634463B1 (en) * | 2005-12-29 | 2009-12-15 | Google Inc. | Automatically generating and maintaining an address book |
| US7685144B1 (en) * | 2005-12-29 | 2010-03-23 | Google Inc. | Dynamically autocompleting a data entry |
| US20070203891A1 (en) * | 2006-02-28 | 2007-08-30 | Microsoft Corporation | Providing and using search index enabling searching based on a targeted content of documents |
| US8117195B1 (en) * | 2006-03-22 | 2012-02-14 | Google Inc. | Providing blog posts relevant to search results |
| US20090171866A1 (en) * | 2006-07-31 | 2009-07-02 | Toufique Harun | System and method for learning associations between logical objects and determining relevance based upon user activity |
| US8200648B2 (en) * | 2006-08-07 | 2012-06-12 | Yeda Research & Development Co. Ltd. At The Weizmann Institute Of Science | Data similarity and importance using local and global evidence scores |
| US20080104128A1 (en) * | 2006-10-24 | 2008-05-01 | Drayer Jay A | system and method for secure, anonymous, and pertinent reposting of private blog posting, etc. |
| US20080154887A1 (en) * | 2006-12-01 | 2008-06-26 | S.L.I. Systems, Inc. | Method and system for displaying information |
| WO2008115519A1 (en) * | 2007-03-20 | 2008-09-25 | President And Fellows Of Harvard College | A system for estimating a distribution of message content categories in source data |
| US7873635B2 (en) * | 2007-05-31 | 2011-01-18 | Microsoft Corporation | Search ranger system and double-funnel model for search spam analyses and browser protection |
| US7664726B2 (en) * | 2007-06-25 | 2010-02-16 | Microsoft Corporation | Influence based rewards for word-of-mouth advertising ecosystems |
| US8010527B2 (en) * | 2007-06-29 | 2011-08-30 | Fuji Xerox Co., Ltd. | System and method for recommending information resources to user based on history of user's online activity |
| US9283476B2 (en) * | 2007-08-22 | 2016-03-15 | Microsoft Technology Licensing, Llc | Information collection during game play |
| US7716228B2 (en) * | 2007-09-25 | 2010-05-11 | Firstrain, Inc. | Content quality apparatus, systems, and methods |
| US8150842B2 (en) * | 2007-12-12 | 2012-04-03 | Google Inc. | Reputation of an author of online content |
| JP2011516938A (en) * | 2008-02-22 | 2011-05-26 | ソーシャルレップ・エルエルシー | Systems and methods for measuring and managing distributed online conversations |
| US8069179B2 (en) * | 2008-04-24 | 2011-11-29 | Microsoft Corporation | Preference judgements for relevance |
| US20100131455A1 (en) * | 2008-11-19 | 2010-05-27 | Logan James D | Cross-website management information system |
| US8694496B2 (en) * | 2008-11-26 | 2014-04-08 | At&T Intellectual Property I, L.P. | Harvesting application metadata |
| US8886636B2 (en) * | 2008-12-23 | 2014-11-11 | Yahoo! Inc. | Context transfer in search advertising |
| US8745067B2 (en) * | 2009-08-12 | 2014-06-03 | Google Inc. | Presenting comments from various sources |
| CA2770868C (en) * | 2009-08-12 | 2014-09-23 | Google Inc. | Objective and subjective ranking of comments |
| US10019518B2 (en) * | 2009-10-09 | 2018-07-10 | Excalibur Ip, Llc | Methods and systems relating to ranking functions for multiple domains |
-
2005
- 2005-09-13 US US11/224,321 patent/US8244720B2/en active Active
-
2006
- 2006-09-13 WO PCT/US2006/035539 patent/WO2007033202A1/en active Application Filing
- 2006-09-13 KR KR1020087008671A patent/KR101005510B1/en active IP Right Grant
- 2006-09-13 BR BRPI0615915A patent/BRPI0615915B1/en active IP Right Grant
- 2006-09-13 CN CNA2006800422026A patent/CN101305371A/en active Pending
- 2006-09-13 EP EP06803458A patent/EP1934830A1/en not_active Ceased
- 2006-09-13 CA CA002622784A patent/CA2622784A1/en not_active Abandoned
- 2006-09-13 AU AU2006290977A patent/AU2006290977B2/en not_active Ceased
- 2006-09-13 JP JP2008531257A patent/JP4837040B2/en active Active
-
2011
- 2011-07-21 JP JP2011159731A patent/JP2011238276A/en active Pending
-
2012
- 2012-06-26 US US13/533,619 patent/US20120265757A1/en not_active Abandoned
Also Published As
| Publication number | Publication date |
|---|---|
| BRPI0615915A2 (en) | 2012-04-10 |
| KR101005510B1 (en) | 2011-01-04 |
| AU2006290977B2 (en) | 2011-04-21 |
| US8244720B2 (en) | 2012-08-14 |
| JP2009508267A (en) | 2009-02-26 |
| KR20080044915A (en) | 2008-05-21 |
| EP1934830A1 (en) | 2008-06-25 |
| JP2011238276A (en) | 2011-11-24 |
| CN101305371A (en) | 2008-11-12 |
| US20120265757A1 (en) | 2012-10-18 |
| JP4837040B2 (en) | 2011-12-14 |
| WO2007033202A1 (en) | 2007-03-22 |
| US20070061297A1 (en) | 2007-03-15 |
| AU2006290977A1 (en) | 2007-03-22 |
| BRPI0615915B1 (en) | 2019-09-10 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US8244720B2 (en) | Ranking blog documents | |
| US7577643B2 (en) | Key phrase extraction from query logs | |
| US8856145B2 (en) | System and method for determining concepts in a content item using context | |
| US7765209B1 (en) | Indexing and retrieval of blogs | |
| US7499940B1 (en) | Method and system for URL autocompletion using ranked results | |
| US8554759B1 (en) | Selection of documents to place in search index | |
| US8150841B2 (en) | Detecting spiking queries | |
| US8762326B1 (en) | Personalized hot topics | |
| US10169449B2 (en) | Method, apparatus, and server for acquiring recommended topic | |
| US7447684B2 (en) | Determining searchable criteria of network resources based on a commonality of content | |
| US20070250501A1 (en) | Search result delivery engine | |
| US20100257171A1 (en) | Techniques for categorizing search queries | |
| US20080082486A1 (en) | Platform for user discovery experience | |
| US20110178995A1 (en) | Microblog search interface | |
| Van Gysel et al. | Reply with: Proactive recommendation of email attachments | |
| US8312011B2 (en) | System and method for automatic detection of needy queries | |
| Batra et al. | Content based hidden web ranking algorithm (CHWRA) | |
| AU2011204929B2 (en) | Ranking blog documents | |
| US8577893B1 (en) | Ranking based on reference contexts | |
| Hendriksen | Extending WASP: providing context to a personal web archive | |
| CN111858684A (en) | Method and system for improving retrieval accuracy based on user checking and recording | |
| Rigaux et al. | Web search |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| EEER | Examination request | ||
| FZDE | Discontinued |
Effective date: 20161116 |