WO2017097061A1

WO2017097061A1 - Smart response method and apparatus

Info

Publication number: WO2017097061A1
Application number: PCT/CN2016/104071
Authority: WO
Inventors: 韩丙卫; 冯军; 丁岩
Original assignee: 中兴通讯股份有限公司
Priority date: 2015-12-07
Filing date: 2016-10-31
Publication date: 2017-06-15
Also published as: CN106844400A

Abstract

A smart response method and apparatus. The method comprises: receiving question information input through a user terminal (S102); searching a plurality of question and answer libraries for a question and answer library corresponding to the type of the question information (S104); searching the question and answer library corresponding to the type of the question information for an answer corresponding to the question information according to a preset rule (S106); and returning an answer corresponding to the question information to the user terminal by serving as a return result (S108). The method resolves the problems in the related art of non-flexible semantic support of a smart question-answering system and inconvenient maintenance, thus improving the flexibility of semantic support, and conveniently maintaining and updating the smart question-answering system.

Description

Intelligent response method and device

Technical field

The present invention relates to the field of communications, and in particular to an intelligent response method and apparatus.

Background technique

The traditional customer service center is mainly based on the telephone call center. However, with the development of the Internet, the increase in the number of users and the diversity of users, the traditional customer service center can not meet the needs of customers. Many large service companies are constantly expanding their more cost-effective customer service centers, reducing labor costs and enhancing user experience, such as smart online customer service and smartphone applications. The core of intelligent customer service is intelligent question and answer. The question and answer system can get short and accurate answers based on user input.

With the extensive research on the question and answer system, the related technologies and products of the intelligent question answering system have aroused great interest from many scientific research institutions and companies at home and abroad. Many products have emerged, which are well adapted to the needs of the market.

In the intelligent customer service system, how to deal with the user input problem, and correctly select the user's required answer from the preset question answer is the core of the system. In the intelligent question and answer, the questions input by the users are not all standard questions, and the standard question and answer pairs stored in the question and answer library are quite different. It is difficult to find the answers that the user wants by using only the search or similarity calculation. Moreover, in the intelligent question answering system in the related art, all the questions and answers are only stored in a question and answer library, the semantic support is not flexible, and the update and maintenance are not convenient.

In view of the related technology, the intelligent question answering system has inflexible semantic support and inconvenient maintenance, and no effective solution has been proposed yet.

Summary of the invention

The embodiment of the invention provides an intelligent response method and device, so as to at least solve the problem that the intelligent question answering system in the related art is inflexible in semantic support and inconvenient to maintain.

According to an aspect of the embodiments of the present invention, an intelligent response method includes: receiving problem information input through a user terminal; searching a plurality of question and answer libraries for a question and answer library corresponding to the type of the problem information; The rule searches for an answer corresponding to the question information from a question answering library corresponding to the type of the question information; and returns an answer corresponding to the question information as a return result to the user terminal.

In the embodiment of the present invention, searching for the answer corresponding to the question information from the question and answer library corresponding to the type of the question information according to the preset rule includes: selecting the question and answer library corresponding to the type of the question information, according to the question information and The similarity of the question stored in the question and answer library corresponding to the type of the problem information, filtering the question in the question answering library corresponding to the type of the problem information; and the corresponding answer corresponding to the filtered question is corresponding to the problem information s answer.

In the embodiment of the present invention, the question information is stored according to the question information and the question and answer library corresponding to the type of the question information. The similarity of the problem, the filtering of the problem in the question answering library corresponding to the type of the problem information includes: obtaining a target problem matching the problem information from the question answering library corresponding to the type of the problem information; obtaining the problem information and the The similarity of the target problem; filtering the target problem in the question and answer library corresponding to the type of the problem information that is less than the preset threshold, and obtaining the first filtering result; when only one target problem is included in the first filtering result, The answer corresponding to the one target question is the answer corresponding to the problem information; when the plurality of the target questions are included in the first filtering result, the target problem corresponding to the highest priority among the plurality of the target questions is taken The answer is the answer to the question information.

In the embodiment of the present invention, the problem information and the similarity value of the target problem are obtained by at least one of the following manners: Mode 1: S=alpha1+beta1*(length2/length1); wherein S represents the problem information and the The similarity value of the target problem; length2 is the information length of the problem information and the information length of the target problem is greater, length1 is the information length of the problem information and the information length of the target problem is smaller; both alpha1 and beta1 are Real number; mode 2: S=alpha*(Samewords/words1+Samewords/words2)/2+beta*dp*(num1/words1+num2/words2); where word1 is the word contained after the word segmentation of the question information Number of words; words2 is the number of words included after the word segmentation of the target question; Samewords is the number of words included after the word segmentation of the question information and the word segmentation of the target question; num1 is The number of words in the wordword that are included in the word segmentation; num2 is the number of words in the wordwords that are segmented for the target question; dp is the minimum value in words1/words2 and words2/words1, a Both lpha and beta are real numbers.

In the embodiment of the present invention, the method 1 is applied to at least one of the following scenarios: the problem information is the same as the target problem; the problem information includes the target problem; and the target problem includes the problem information.

In the embodiment of the present invention, the number of words included in the segmentation of the problem information is obtained by the following rules: segmenting the problem information to obtain a plurality of words; assigning each word according to the part of speech of each word Weighting; the number of each of the plurality of words and the weighted sum of each of the words as the number of words included after the word segmentation of the question; the following rules are used to obtain the word segmentation after the target problem is included The number of words: segmentation of the target question, obtaining a plurality of words; assigning a weight to each of the words according to the part of speech of each word; the number of each of the plurality of words and each of the words The weighted sum of words is the number of words included after the word segmentation of the target question.

In the embodiment of the present invention, searching, from a plurality of question and answer libraries, the question and answer library corresponding to the type of the problem information includes: determining whether the problem information is the first type of problem information; and the problem information is the first type of problem In the case of information, obtaining a first type of question and answer library corresponding to the first type of question information; and if the question information is not the first type of question information, determining whether the question information is the second type of question information; When the problem information is the second type of problem information, the second type of question answering library corresponding to the second type of question information is obtained; from the second type of question answering library, the problem information is reconfirmed according to the preset rule; The reconfirmed question information is the third type of question information; in the case where the reconfirmed question information is the third type of question information, the third type of question answering library corresponding to the reconfirmed question information is obtained.

In the embodiment of the present invention, the first type of problem information includes: slang; the first type of question and answer library includes: a slang corpus; wherein the slang corpus stores a slang word and an answer corresponding to the slang word; The second type of problem information includes: specific problem information; the second type of question and answer library includes: an equivalence sentence and a standard sentence library; wherein the equivalence sentence and the standard sentence library store the specific problem and correspond to the specific problem a standard sentence or an equivalent sentence; the third type of problem information includes: general problem information; the third type of question and answer library includes: a general question and an answer corresponding to the ordinary question.

In the embodiment of the present invention, from the second type of question and answer library, reconfirming the problem information according to the preset rule includes: querying, from the second type of question and answer library, all the questions corresponding to the problem information; After the rule is filtered to obtain all the second filtering results, if the second filtering result is unique, the filtering result is used as the re-confirmed problem information; in the case where the second filtering result does not exist Next, the problem information input through the user terminal is used as the problem information after the reconfirmation.

In the embodiment of the present invention, before returning the answer corresponding to the problem information to the user terminal as a return result, the method further includes: determining whether the answer corresponding to the problem information is the fourth type of problem information; wherein The fourth type of problem information includes: a guided question; if yes, triggering display of the prompt information, wherein the prompt information is used to prompt the user terminal to input the guide information corresponding to the fourth type of problem information; if not, directly The answer corresponding to the question information is returned to the user terminal as a return result.

According to another embodiment of the present invention, an intelligent response apparatus is provided, including: a receiving module configured to receive problem information input through a user terminal; and a first searching module configured to search from a plurality of question and answer libraries a question answering library corresponding to the type of the problem information; the second searching module is configured to search for an answer corresponding to the question information from the question answering library corresponding to the type of the question information according to the preset rule; and returning the module, set to be The answer corresponding to the question information is returned to the user terminal as a return result.

In the embodiment of the present invention, the second searching module is further configured to: according to the problem information, the similarity between the problem information and the question stored in the question and answer library corresponding to the type of the problem information, from the question answering library corresponding to the type of the problem information. Filtering the question in the question and answer library corresponding to the type of the problem information; and using the filtered answer corresponding to the question as the answer corresponding to the question information.

In the embodiment of the present invention, the second searching module includes: a first acquiring unit, configured to acquire a target problem that matches the problem information from a question and answer library corresponding to the type of the problem information; and the second obtaining unit is configured to Obtaining a similarity between the problem information and the target problem; the filtering unit is configured to filter the target problem in the Q&A library corresponding to the type of the problem information that is less than a preset threshold, to obtain a first filtering result; In order to include only one of the target questions in the first filtering result, the answer corresponding to the one target question is used as an answer corresponding to the problem information; and when the plurality of the target questions are included in the first filtering result, The answer corresponding to the target question with the highest priority among the plurality of the target questions is taken as the answer corresponding to the question information.

In the embodiment of the present invention, the second obtaining unit acquires the similarity value of the problem information and the target problem by using at least one of the following manners: mode 1: S=alpha1+beta1*(length2/length1); wherein, S represents The similarity value between the problem information and the target problem; length2 is the information length of the problem information and the information length of the target problem is greater, and length1 is the information length of the problem information and the information length of the target problem is smaller; Both alpha1 and beta1 are real numbers; mode two: S=alpha*(Samewords/words1+Samewords/words2)/2+beta*dp*(num1/words1+num2/words2); where word1 is the word segmentation of the problem information The number of words included after the word; word2 is the number of words included after the word segmentation of the target question; Samewords is the same word included after the word segmentation of the question information is segmented after the word segmentation of the target question Number: num1 is the number of words in the wordwords that are segmented for the problem information; num2 is the number of words in the wordwords that are segmented for the target question; dp is words1/words2 and words2/word The minimum value in s1, alpha and beta are both real numbers.

In the embodiment of the present invention, the first searching module includes: a first determining unit, configured to determine whether the problem information is the first type of problem information; and a third obtaining unit, configured to: the problem information is the first type of problem In the case of information, a first type of question and answer library corresponding to the first type of question information is obtained; and the second determining unit is configured to determine whether the question information is the first if the question information is not the first type of question information. a second type of problem information, wherein the fourth obtaining unit is configured to obtain a second type of question and answer library corresponding to the second type of question information if the problem information is the second type of question information; and the confirming unit is set to be from the first In the second type of question answering library, the problem information is reconfirmed according to the preset rule; the third determining unit is configured to determine whether the reconfirmed question information is the third type of problem information; and the fifth obtaining unit is set to reconfirm the In the case where the problem information is the third type of problem information, a third type of question answering library corresponding to the reconfirmed problem information is obtained.

In the embodiment of the present invention, the confirmation unit includes: a query subunit, configured to query all the questions corresponding to the problem information from the second type of question and answer library; and the filtering subunit is set to follow the preset rule After filtering all the questions, the second filtering result is obtained; the confirmation subunit is set to use the filtering result as the problem information after the reconfirmation if the second filtering result is unique; and in the absence of the second filtering In the case of the result, the problem information input by the user terminal is used as the problem information after the reconfirmation.

In the embodiment of the present invention, the device further includes: a determining module, configured to determine whether the answer corresponding to the problem information is the fourth type of problem information; wherein the fourth type of problem information includes: a guided question; a display module, When the answer corresponding to the question information is the fourth type of question information, triggering the display of the prompt information, wherein the prompt information is used to prompt the user terminal to input the guide information corresponding to the fourth type of problem information; The returning module is further configured to directly return the answer corresponding to the question information as a return result to the user terminal if the answer corresponding to the question information is not the fourth type of question information.

Embodiments of the present invention also provide a storage medium, which may be configured to store program code for performing the following steps: receiving problem information input through a user terminal; searching for the problem from a plurality of question and answer libraries A question answering library corresponding to the type of information; searching for an answer corresponding to the question information from a question and answer library corresponding to the type of the question information according to a preset rule; and returning the answer corresponding to the question information as a return result to the user terminal.

Through the embodiment of the present invention, the problem information input through the user terminal is received; from the plurality of question and answer libraries, the question and answer library corresponding to the type of the problem information is searched; and the question and answer library corresponding to the type of the problem information is selected according to the preset rule. Find an answer corresponding to the question information; return the answer corresponding to the question information as a return result to the user terminal. The question and answer library is divided into multiple question and answer libraries. According to the type of the question information input, the answers corresponding to the question information are searched from the question and answer library corresponding to the type of the question information in the plurality of question and answer libraries, and the intelligence in the related technology is solved. The question and answer system has inflexible semantic support and inconvenient maintenance, which improves the flexibility of semantic support and facilitates the maintenance and update of the intelligent question answering system.

DRAWINGS

The drawings described herein are intended to provide a further understanding of the invention, and are intended to be a part of the invention. In the drawing:

1 is a flowchart 1 of an intelligent response method according to an embodiment of the present invention;

2 is a second flowchart of an intelligent response method according to an embodiment of the present invention;

3 is a third flowchart of an intelligent response method according to an embodiment of the present invention;

4 is a flowchart 4 of an intelligent response method according to an embodiment of the present invention;

5 is a flow chart of a smart question answering method in accordance with a preferred embodiment of the present invention;

6 is a schematic flow chart of a query question and answer process according to a preferred embodiment of the present invention;

7 is a structural block diagram 1 of an intelligent response device according to an embodiment of the present invention;

FIG. 8 is a structural block diagram 2 of an intelligent response apparatus according to an embodiment of the present invention; FIG.

FIG. 9 is a structural block diagram 3 of an intelligent response apparatus according to an embodiment of the present invention; FIG.

FIG. 10 is a structural block diagram 4 of an intelligent response apparatus according to an embodiment of the present invention; FIG.

FIG. 11 is a structural block diagram 5 of an intelligent response apparatus according to an embodiment of the present invention; FIG.

12 is a block diagram showing the architecture of a smart question answering system in accordance with a preferred embodiment of the present invention.

detailed description

The invention will be described in detail below with reference to the drawings in conjunction with the embodiments. It should be noted that the embodiments in the present application and the features in the embodiments may be combined with each other without conflict.

It is to be understood that the terms "first", "second" and the like in the specification and claims of the present invention are used to distinguish similar objects, and are not necessarily used to describe a particular order or order.

An intelligent response method is provided in this embodiment. FIG. 1 is a flowchart 1 of an intelligent response method according to an embodiment of the present invention. As shown in FIG. 1 , the process includes the following steps:

Step S102, receiving problem information input through the user terminal;

Step S104, searching for a question and answer library corresponding to the type of the problem information from the plurality of question and answer libraries;

Step S106, searching for an answer corresponding to the problem information from a question and answer library corresponding to the type of the problem information according to a preset rule;

In step S108, the answer corresponding to the question information is returned to the user terminal as a return result.

Due to the intelligent answering system in the related art, all the questions and answers are only stored in a question and answer library, which is not convenient for updating and maintaining the question and answer library. Through the above steps, the question and answer library is divided into multiple, different questions. The type of information corresponds to different question and answer libraries, that is, different question and answer libraries store different types of questions and answers. When receiving the input question information, the type of the question information is from the question and answer library corresponding to the type of the question information. To find the answer corresponding to the problem information, enhance the semantic support ability, improve the speed of question and answer, and at the same time, because different question and answer libraries store different types of questions and answers, it is more convenient to answer the library for targeted Update and maintenance to solve the phase In the technology, the intelligent question answering system is inflexible in semantic support and inconvenient to maintain.

It should be noted that the above problem information may include: "Hello", "How is the weather" and the like, with certain characteristics such as using dialects to describe how to query the specific fee information, etc., "How to check the phone bill" Ordinary problem information such as "how to send a text message", a guided question such as "query call charge"; the types of the above question and answer library may include: a slang corpus, an equivalent sentence and a standard sentence library, and a general question and answer library; The slang corpus stores a slang word and an answer corresponding to the slang word; the equivalent sentence and the standard sentence library store the specific question and a standard sentence or an equivalent sentence corresponding to the specific question; Stores common questions and answers to the common questions. Each type of question information corresponds to a type of question and answer library.

In an embodiment of the present invention, the step S104 may include: selecting, from the question and answer library corresponding to the type of the problem information, the similarity of the problem information and the question stored in the question and answer library corresponding to the type of the question information. Filtering the question in the question and answer library corresponding to the type of the problem information; and using the filtered answer corresponding to the question as the answer corresponding to the question information. Specifically, the method may be: obtaining a target problem that matches the problem information from a question and answer library corresponding to the type of the problem information; obtaining a similarity between the problem information and the target problem; filtering the type of the problem information In the corresponding question and answer library, the target problem with the similarity less than the preset threshold is obtained, and the first filtering result is obtained; when only one target problem is included in the first filtering result, the answer corresponding to the target problem is taken as the problem The answer corresponding to the information; when the plurality of the target questions are included in the first filtering result, the answer corresponding to the target question with the highest priority among the plurality of the target questions is taken as the answer corresponding to the problem information.

It should be noted that the above-mentioned target problem may be a problem related to the problem information, and the related questions are found in the question and answer library corresponding to the type of the problem information, and the similarity between the problem information and the related problems is calculated. First, the related problems whose similarity is less than a certain threshold are filtered out. If there is only one related problem after filtering, the answer corresponding to the related question is taken as the answer corresponding to the problem information; if it is filtered out, When multiple related questions are concerned, the answer corresponding to the question with the highest priority may be taken as the answer corresponding to the question information according to the priority of the related questions. It should be noted that the priority may be the ranking score of the search engine of the related question, and the priority of the ranked high is high. That is to find the answer corresponding to the problem information through the combination of search and similarity filtering, and solve the problem that the search engine hits too many results in the related art, can not directly return to the user's answer, and overcomes the common similarity. Calculate the problem of weak semantic support.

The preset threshold may be preset, may be a fixed value, or may be adjusted in real time according to actual conditions, and the preset threshold may be set as empirical data.

In an embodiment of the present invention, the problem information and the similarity value of the target problem are obtained by at least one of the following manners: Mode 1: S=alpha1+beta1*(length2/length1); wherein S represents the problem information The similarity value with the target problem; length2 is the information length of the problem information and the information length of the target problem is greater, length1 is the information length of the problem information and the information length of the target problem is smaller; alpha1 and beta1 Both are real numbers; mode two: S=alpha*(Samewords/words1+Samewords/words2)/2+beta*dp*(num1/words1+num2/words2); where word1 is included after the word segmentation of the problem information The number of words; words2 is the number of words included after the word segmentation of the target question; Samewords is the number of words included in the word segmentation after the word segmentation is performed after segmentation of the target question; Num1 is the number of words in the Samewords that are segmented after the problem information is included; Num2 is the number of words in Samewords that are segmented for the target problem; dp is the minimum value of words1/words2 and words2/words1, alpha and beta are both real numbers; words1/words2 is the ratio of words1 to words2, Words2/words1 is the ratio of words2 to words1.

In an embodiment of the present invention, the number of words included in the word segmentation of the problem information may be obtained by dividing the problem information into a plurality of words; each word of the word is used for each word. The word assigns a weight; the number of each of the plurality of words and the weighted sum of the words are the number of words included after the word segmentation of the question information; the target problem can be obtained by the following rules The number of words included after the word segmentation: segmentation of the target question, obtaining a plurality of words; assigning a weight to each word according to the part of speech of each word; the number of each word of the plurality of words And the weighted sum of each word as the number of words included after the word segmentation of the target question.

It should be noted that the weights of different part-of-speech allocations are different. For example, the weight of a noun can be 2, the weight of a verb can be 2, and the weight of an adjective is 1, wherein a weight of 1 means that when calculating the total number of words included, The word is only calculated once. If the weight is 2, it means that when calculating the total number of words included, the word needs to be calculated twice. For example, the question information is the query for the month of January; the word segmentation is used to get 3 words: the query (verb) In January (adjective), telephone charge (noun); according to the verb and noun part of the weight of 2, the adjective weight is 1, then the number of words in the question information after the word segmentation is calculated, the query counts 2 The word counts 1 word in January, and the phone bill counts 2 words; that is, the number of words included in the question information after the word segmentation is 2+1+2=5.

It should be noted that the foregoing manner 1 may be applied to at least one of the following scenarios: the problem information is the same as the target problem; the problem information includes the target problem; and the target problem includes the problem information. In addition to the above scenarios, mode 2 may be employed, but is not limited thereto.

In an embodiment of the present invention, FIG. 2 is a flowchart 2 of an intelligent response method according to an embodiment of the present invention. As shown in FIG. 2, the foregoing step S104 may include:

Step S104-1, determining whether the problem information is the first type of problem information;

Step S104-2, if the problem information is the first type of problem information, acquiring a first type of question answering library corresponding to the first type of problem information;

Step S104-3, if the problem information is not the first type of problem information, determining whether the problem information is the second type of problem information;

Step S104-4, if the problem information is the second type of problem information, acquiring a second type of question answering library corresponding to the second type of problem information;

Step S104-5, from the second type of question and answer library, re-confirm the problem information according to the preset rule;

Step S104-6, determining whether the reconfirmed problem information is the third type of problem information;

Step S104-7, in the case where the reconfirmed problem information is the third type of question information, acquire a third type of question answering library corresponding to the reconfirmed question information.

In the embodiment of the present invention, the first type of problem information may include: the above-mentioned slang language; the above-mentioned first type question and answer The library includes: the above-mentioned slang corpus; the second type of problem information may include: specific problem information; the second type of question and answer library may include: an equivalent sentence and a standard sentence library; the third type of problem information may include: general problem information The third type of question and answer library mentioned above may include: a general question and answer library.

It should be noted that the above specific problem may be some personalized problem. For these personalized problems, the corresponding answer is found by searching for the equivalent sentence or standard sentence corresponding to the equivalent sentence and the standard sentence database. .

In an embodiment of the present invention, FIG. 3 is a flowchart of a smart response method according to an embodiment of the present invention. As shown in FIG. 3, the foregoing step S212 may include:

Step S212-1, querying, from the second type of question and answer library, all the questions corresponding to the problem information;

Step S212-2, after filtering all the questions according to the preset rule, obtaining a second filtering result;

Step S212-3, in the case that the second filtering result is unique, the filtering result is used as the re-confirmed problem information; and in the case where the second filtering result does not exist, the problem information input through the user terminal is to be As the problem information after the reconfirmation.

It should be noted that the preset rule may be the similarity filtering mode described above, and the problem of low similarity is filtered out by setting the threshold value by calculating the similarity between the problem information and all the questions corresponding to the problem information. The remaining question may be the issue of reconfirmation.

In an embodiment of the present invention, FIG. 4 is a flowchart of a smart response method according to an embodiment of the present invention. As shown in FIG. 4, before the step S108, the method may further include:

Step S402, determining whether the answer corresponding to the problem information is the fourth type of problem information; wherein the fourth type of problem information includes: a guided question;

Step S404, if yes, triggering display of the prompt information, wherein the prompt information is used to prompt the user terminal to input the guide information corresponding to the fourth type of problem information;

Step S406, if not, directly returning the answer corresponding to the question information to the user terminal as a return result.

It should be noted that the above-mentioned guided question may be an extension of the ordinary question and answer. The guided question cannot directly obtain the answer, and must obtain some necessary information through interactive guidance to obtain the final result.

For example, if you enter "query call charge", you need to guide the user to enter the mobile phone number, month and other information to get the final answer. The guide problem is "query call charge", and the guide information is mobile phone number, month and other information.

It should be noted that, before the step S104, the method further includes: determining whether the problem information includes a sensitive word, and if the sensitive word is included, performing step S104 to step S108 instead of directly returning, indicating that the sensitive word is included; If the sensitive word is not included, step S104 is performed. It should be noted that sensitive words can be words such as illegal drugs, yellow-related and other illegal laws.

In order to better understand the embodiments of the present invention, the present invention is further explained in conjunction with the preferred embodiments.

The present invention provides a preferred intelligent question answering method. In the preferred embodiment, the user input problem is required. Class, in the intelligent question answering system, the user's input can be divided into the following categories:

Ordinary greetings (equivalent to the slang in the above examples): such as "Hello", "How is the weather", etc.

Ordinary question and answer (equivalent to the general problem information in the above embodiment): The ordinary question and answer is that the user enters a question and wants to directly obtain the answer to the question. The difference with a normal search engine is that the search engine returns multiple answers to a question, requiring the user to select the desired result from multiple answers; and the intelligent question answering system directly returns the most similar answer to the user.

Guided question and answer (equivalent to the guided question in the above embodiment): Guided question and answer is an extension of the general question and answer. A question cannot be directly obtained. It must be interactively guided to obtain some necessary information before the final result can be obtained. If the user enters "query call charge", this question must guide the user to enter the mobile phone number, month and other information to get the final answer.

The intelligent question answering system has different processing logic depending on the type of problem.

In addition, in the preferred embodiment, the question answering library in the intelligent question answering system is divided into the following types, and the corresponding data is saved through the following question and answer library:

The chilling database (corresponding to the slang corpus in the above embodiment): the corpus of the chilling dialogue such as the slang and the answer corresponding to the slang, the data is saved to the system index library (corresponding to the slang corpus in the above embodiment).

The general question and answer library (equivalent to the general question and answer library in the above embodiment): the general problem and the answer corresponding to the common question, and the corpus of the guided question.

Equivalent sentence and standard sentence library (equivalent to the equivalent sentence and standard sentence library in the above embodiment): Save the standard sentence corresponding to the personalized question and the personalized question. In the intelligent question answering system, the general question and answer library stores The standard question and the answer corresponding to the standard question, this corpus is relatively small, and in the formal intelligent question answering system, the user input problem is in various forms, and the equivalent sentence and the standard sentence library also store the user input problem and Correspondence of standard questions.

Based on the above, the above preferred intelligent question and answer method may include the following steps:

Step 1, the user enters a question;

Step 2: The sensitive word determination includes the following steps: Step 21: Determine whether the input contains a sensitive word, if the sensitive word is included, perform step 22, and do not include performing step 31; Step 22, including the sensitive word, directly returning, and not continuing, The prompt contains sensitive words;

Step 3: Hanyu judgment: Step 31: Determine whether the user input is a slang word, search from the slang corpus, and if the searched result has a value after threshold filtering, the input question is considered to be a chilling conversation; step 32, if input Is a cold dialogue, choose one of the results to return to the user, do not continue to execute; if it is not a cold dialogue, go to step 41;

Step 4: Equivalence sentence search and standard question replacement: Step 41: Using the user input question as a query condition, querying in the equivalence sentence and the standard sentence library, and querying all relevant results; Step 42, performing similarity on the query result Calculate, if there is a unique result after filtering the calculation result, replace the standard question of the result with the user's input question, if not Exist, retain the original problem;

Step 5: Search the question and answer library: Step 51, after processing in step 4, search the general question and answer library with the processed question, and query all relevant results; Step 52, perform the similarity calculation on the query result, and if there is a unique result after filtering the calculation result For a result, the result is taken as a question and answer record, and the answer field of the record is taken as a pre-return result.

In step 6, the process is arranged to determine whether the result is a guided problem: in step 61, after the step 5 is processed, the pre-return result is subjected to the guided question determination; and in step 62, if the guided question has subsequent processing, the process is performed. The arrangement process prompts the user to input; step 63, if it is not a guided question, directly returns the pre-return result as an answer to the user.

It should be noted that step 1 corresponds to step S102 in the above embodiment, and steps 2 to 4 correspond to steps S202 to S214 in the above embodiment; step 5 corresponds to step S108, and step 6 corresponds to the above steps. S402 to step S406.

In a preferred embodiment of the present invention, the similarity calculation method may be: parameter 1: user input (corresponding to problem information in the above embodiment) parameter 2: search result (corresponding to the target problem in the above embodiment), The above similarity calculation method includes steps S1 to S6:

Step S1: If the user input is exactly the same as the search result, the similarity is 1.0; if the parameter 1 contains the parameter 2, or the parameter 2 includes the parameter 1 to perform the step S2; otherwise, the step S3 is performed.

In step S2, the longer value of the parameter is length1 and the other is length2, and the similarity score is calculated: alpha1+beta1*length2/length1; the calculation result is returned. Among them, the alpha1 and beta1 are empirical values.

Step S3, performing word segmentation and part-of-speech tagging on user input and search results.

Step S4, adjusting the weight after the word segmentation, the noun and the verb are adjusted to 2, and the other parts of speech are unchanged.

Step S5, the number of the same words after the statistical parameter 1 and the parameter 2 word segmentation, the weight is 2, calculated twice, and the count is samewords.

Step S6, after the parameter 1 word segmentation is words1, after the parameter 2 word segmentation is words2, the samewords contains the number of words in the word1 is num1, and the samewords contains the number of words in the words2 is num2. The algorithm for specific similarity is:

Double dp=Math.min(1.0*words1.size()/words2.size(),1.0*words2.size()/words1.size());

Double part1=alpha*(1.0*samewords.size()/words1.size()+1.0*samewords.size()/words2.size())/2.0;

Double part2=beta*dp*(num1/words1.size()+num2/words2.size())/2.0;

The similarity is the value of part1+part2, where size() in the preferred embodiment is used to calculate the number of elements.

In the preferred embodiment, the threshold filtering method includes the following steps 1 to 4:

Step 1, calculating the phase of the input question and the search hit result problem (corresponding to the target problem in the above embodiment) field Similarity

Step 2: The similarity threshold is taken, and all the result problems whose similarity is less than the similarity threshold are filtered out; wherein the similarity threshold (similarityThreshold)=percent*maximum similarity, wherein the percentage is an empirical value;

Step 3: If after step 1, 2, only one problem result remains after processing, the result is the final result, and the answer field value is returned from the result. If the result of the problem after the processing of steps 1 and 2 is greater than one, the remaining results are filtered by the ranking of the search engine searched from the question and answer library, and the item with the highest sorting score (scoreMax) is taken as the final result. Filter out the remaining problem results.

Step 4: After the processing in step 3, if the final result is one, the result is the final result, and the answer field value is returned from the result.

Another preferred intelligent question answering method is also provided in the embodiment of the present invention. As shown in FIG. 5, the smart question answering method includes:

Step S502, the user inputs a question;

Step S504, it is determined whether the session is set (session); if not, step S506 is performed; in the case of YES, step S508 is performed;

Step S506, performing a normal search;

Step S508, the robot searches whether the question input by the user contains a sensitive word; if it is included, step S510 is performed; if not, step S512 is performed;

Step S510, returning directly, reminding the user to include the sensitive word;

Step S512, normalizing the problem input by the user, such as special symbol processing;

Step S514, it is determined whether the session exists and there is a cache; if yes, step S516 is performed; if not, step S522 is performed;

Step S516, performing guided problem processing;

Step S518, it is determined whether the guided problem is processed normally, in the case of normal processing, step S520 is performed; if the processing is not normal, step S522 is performed;

Step S520, caching the problem, and returning the result;

Step S522, it is determined whether the problem is a slang; if yes, step S524 is performed; if not, step S526 is performed;

Step S524, returning to the dialogue;

Step S526, querying the question and answer processing flow;

Step S528, the result number is obtained, in the case that the number of results is 1, step S530 is performed; in the case where the number of results is 0, step S532 is performed; and in the case where the number of results is greater than 1, step S534 is performed;

Step S530, it is determined whether it is a guided question, if yes, step S536 is performed; if not, step S538 is performed;

Step S532, determining context information; performing step S538;

Step S534, updating the result;

Step S536, interaction problem processing;

Step S538, updating the result and buffering the update result;

In step S540, the result is returned.

In the above preferred embodiment, step S526 can be implemented by the following process. As shown in FIG. 6, the process includes steps S602 to S626:

Step S602, accurately querying the equivalent sentence in the equivalent sentence and the standard sentence library;

Step S604, it is determined whether an equivalence sentence is found, if yes, step S606 is performed; if not, step S608 is performed;

Step S606, performing standard sentence replacement;

Step S608, using regular expression matching;

Step S610, it is determined whether the unique result is matched; if yes, step S606 is performed;

Step S612, searching for the standard sentence in the general question and answer library;

Step S614, performing similarity filtering;

Step S616, it is determined whether there is a problem result corresponding to the standard sentence after the similarity filtering; if not, step S618 is performed; if yes, step S626 is performed;

Step S618, the word segmentation query standard sentence; the standard sentence is divided into words, and the problem corresponding to the standard sentence is segmented;

Step S620, performing similarity filtering;

Step S622, it is determined whether there is a unique problem result corresponding to the standard sentence after filtering; if yes, step S624 is performed;

Step S624, searching the general question and answer library to query the answer;

In step S626, the number of answers is obtained.

It should be noted that the specific similarity calculation method is the same as that shown in the above steps S1 to S6, and the similarity filtering is the same as the manner shown in the above steps 1 to 4.

Through the description of the above embodiments, those skilled in the art can clearly understand that the method according to the above embodiment can be implemented by means of software plus a necessary general hardware platform, and of course, by hardware, but in many cases, the former is A better implementation. Based on such understanding, the technical solution of the present invention, which is essential or contributes to the prior art, may be embodied in the form of a software product stored in a storage medium (such as ROM/RAM, disk, CD-ROM, including a number of instructions to make a terminal device (can be a mobile phone, a computer, The server, or network device, etc.) performs the methods described in various embodiments of the present invention.

An intelligent response device is also provided in the embodiment, which is used to implement the above-mentioned embodiments and preferred embodiments, and has not been described again. As used below, the term "module" may implement a combination of software and/or hardware of a predetermined function. Although the apparatus described in the following embodiments is preferably implemented in software, hardware, or a combination of software and hardware, is also possible and contemplated.

FIG. 7 is a structural block diagram 1 of an intelligent response apparatus according to an embodiment of the present invention. As shown in FIG. 7, the apparatus includes:

The receiving module 72 is configured to receive the problem information input through the user terminal;

The first searching module 74 is connected to the receiving module 72, and is configured to search for a question and answer library corresponding to the type of the problem information from the plurality of question and answer libraries;

The second searching module 76 is connected to the first searching module 74, and is configured to search for an answer corresponding to the problem information from a question and answer library corresponding to the type of the problem information according to a preset rule.

The returning module 78 is connected to the second searching module 76, and is configured to return the answer corresponding to the question information to the user terminal as a return result.

After the receiving module 72 receives the input problem information, the first searching module 74 and the second searching module 76 search for the problem information from the question and answer library corresponding to the type of the problem information. The answer corresponding to the problem information, that is, by dividing the question and answer library into multiples, the types of different problem information correspond to different question and answer libraries, that is, different question and answer libraries store different types of questions and answers, compared with the intelligence in related technologies. The response system enhances the semantic support ability and improves the speed of question and answer. At the same time, because different question and answer libraries store different types of questions and answers, it is more convenient to solve the problematic library for targeted update and maintenance. In the related art, the intelligent question answering system is inflexible in semantic support and inconvenient to maintain.

In an embodiment of the present invention, the second searching module 76 is further configured to: according to the question information and the question stored in the question and answer library corresponding to the type of the question information, from the question answering library corresponding to the type of the question information. The similarity degree is filtered by the question and answer library corresponding to the type of the problem information; the filtered answer corresponding to the question is used as the answer corresponding to the question information. Specifically, FIG. 8 is a structural block diagram of an intelligent response apparatus according to an embodiment of the present invention. As shown in FIG. 8, the second searching module 76 includes:

The first obtaining unit 82 is configured to obtain, from the question and answer library corresponding to the type of the problem information, the problem information Target problem

The second obtaining unit 84 is connected to the first acquiring unit 82, and is configured to acquire the similarity between the problem information and the target problem;

The filtering unit 86 is connected to the second obtaining unit 84, and is configured to filter a target problem in the Q&A library corresponding to the type of the problem information that is less than a preset threshold, to obtain a first filtering result;

The searching unit 88 is connected to the filtering unit 86, and is configured to: when the first filtering result includes only one target question, the answer corresponding to the one target question is used as an answer corresponding to the problem information; and at the first When the plurality of the target questions are included in the filtering result, the answer corresponding to the target question with the highest priority among the plurality of the target questions is taken as the answer corresponding to the problem information.

It should be noted that the foregoing target problem may be a problem related to the problem information, and the second searching module 76 finds related problems in the question and answer library corresponding to the type of the problem information, and calculates the problem information and the correlation. The similarity of the problem, first filter out the related problems whose similarity is less than a certain threshold. If there is only one related problem after filtering, the answer corresponding to the related question is taken as the answer corresponding to the problem information; If there are multiple related problems after filtering out, the answers corresponding to the questions with the highest priority can be taken as the answers corresponding to the problem information according to the priority of these related questions. It should be noted that the priority may be the ranking score of the search engine of the related question, and the priority of the sorted high is high. That is to find the answer corresponding to the problem information through the combination of search and similarity filtering, and solve the problem that the search engine hits too many results in the related art, can not directly return to the user's answer, and overcomes the common similarity. Calculate the problem of weak semantic support.

In an embodiment of the present invention, the second obtaining unit 84 may obtain the similarity value of the problem information and the target problem in at least one of the following manners: Mode 1: S=alpha1+beta1*(length2/length1); Wherein, S represents the similarity value of the problem information and the target problem; length2 is the information length of the problem information and the information length of the target problem, and length1 is the information length of the problem information and the information length of the target problem. The smaller ones; both alpha1 and beta1 are real numbers; mode two: S=alpha*(Samewords/words1+Samewords/words2)/2+beta*dp*(num1/words1+num2/words2); where word1 is the The number of words included in the problem information after word segmentation; words2 is the number of words included after the word segmentation of the target question; Samewords is the word included after the word segmentation of the question information and the word segmentation of the target question The number of the same word; num1 is the number of words after the word segmentation included in Samewords; num2 is the number of words in the Samewords after the word segmentation of the target question; dp is words1/wor The minimum values in ds2 and words2/words1, alpha and beta are both real numbers.

The second obtaining unit 84 may obtain the number of words included after the word segmentation of the problem information by using the following rule: segmenting the problem information to obtain a plurality of words; each of the words according to the part of the word a word assigning weight; the number of each of the plurality of words and the weighted sum of each of the words as the number of words included after the word segmentation of the question information; the word segmentation of the target question can be obtained by the following rules The number of words included after: segmentation of the target question, obtaining a plurality of words; assigning a weight to each of the words according to the part of speech of each word; the number of each of the plurality of words Each The weighted sum of words is the number of words included after the word segmentation of the target question.

FIG. 9 is a structural block diagram 3 of an intelligent response apparatus according to an embodiment of the present invention. As shown in FIG. 9, the first search module 74 may include:

The first determining unit 92 is configured to determine whether the problem information is the first type of problem information;

The third obtaining unit 94 is connected to the first determining unit 92, and is configured to acquire a first type of question answering library corresponding to the first type of question information if the problem information is the first type of question information;

The second determining unit 96 is connected to the third acquiring unit 94, and is configured to determine whether the problem information is the second type of problem information if the problem information is not the first type of problem information;

The fourth obtaining unit 98 is connected to the second determining unit 96, and is configured to acquire a second type of question answering library corresponding to the second type of question information if the question information is the second type of question information;

The confirmation unit 910 is connected to the fourth obtaining unit 98, and is configured to re-confirm the problem information according to the preset rule from the second type of question and answer library;

The third determining unit 912 is connected to the confirming unit 910, and is configured to determine whether the reconfirmed question information is the third type of problem information;

The fifth obtaining unit 914 is connected to the third determining unit 912, and is configured to acquire a third type of question answering library corresponding to the reconfirmed question information if the reconfirmed question information is the third type of question information.

In the embodiment of the present invention, the first type of problem information may include: the above-mentioned slang; the first type of question and answer library may include: the slang corpus; the second type of problem information may include: specific problem information; The quiz library may include: an equivalence sentence and a standard sentence library; the third type of problem information may include: general problem information; the third type of question and answer library may include: a general question and answer library.

FIG. 10 is a block diagram showing the structure of an intelligent response device according to an embodiment of the present invention. As shown in FIG. 10, the confirmation unit 910 may include:

The query subunit 1002 is configured to query all questions corresponding to the problem information from the second type of question and answer library;

The filtering subunit 1004 is connected to the query subunit 1002, and is configured to filter all the questions according to the preset rule to obtain a second filtering result.

The confirmation subunit 1006 is connected to the filtering subunit 1004, and is configured to use the filtering result as the problem information after the reconfirmation when the second filtering result is unique; and in the case where the second filtering result does not exist Next, the problem information input through the user terminal is used as the problem information after the reconfirmation.

Figure 11 is a block diagram showing the structure of an intelligent response device according to an embodiment of the present invention. As shown in Figure 11, the device further includes:

The determining module 1102 is configured to determine whether the answer corresponding to the problem information is the fourth type of problem information; wherein the fourth type of problem information includes: a guided question;

The display module 1104 is connected to the determining module 1102, and is configured to trigger the display of the prompt information when the answer corresponding to the question information is the fourth type of question information, wherein the prompt information is used to prompt the user terminal to input and Guidance information corresponding to the fourth type of problem information;

The returning module 78 is further configured to directly return the answer corresponding to the question information as a return result to the user terminal if the answer corresponding to the question information is not the fourth type of question information.

It should be noted that the foregoing apparatus may further include another determining module, and is connected to the receiving module 72, and is configured to determine whether the problem information includes a sensitive word, and if the sensitive word is included, the answer corresponding to the problem information is not queried. Instead, it returns directly, the prompt contains sensitive words; if the sensitive words are not included, the first search module 74, the second search module 76, and the return module 78 continue to work. It should be noted that sensitive words can be words such as illegal drugs, yellow-related and other illegal laws.

For a better understanding of the invention, the invention will be further explained in conjunction with the preferred embodiments.

The present invention provides an architectural diagram of a smart question answering system of a preferred embodiment, and FIG. 12 is a schematic structural diagram of a smart question answering system according to a preferred embodiment of the present invention. As shown in FIG. 12, the smart question answering system includes: a management platform 1202, Search engine module 1204, interactive question and answer service module 1206;

The interactive question answering service module 1206 includes: a sensitive word filtering module 1208, configured to determine a user input question. Whether the sensitive word is included; the greeting dialog module 1210 (corresponding to the first determining unit 92 in the above embodiment) is configured to determine whether the question input by the user is a slang; the equivalent sentence and the standard sentence conversion module 1212 (equivalent to the above implementation) The second judging unit 96 and the fourth obtaining unit 98) in the example are configured to convert the question input by the user into an equivalent sentence or a standard sentence; the regular expression matching module 1214 is set to not find a problem corresponding to the question input by the user. In the case of an equivalent sentence, the regular input matching is performed on the question input by the user; the participle part-of-speech tagging module 1216 is set to segment the question input by the user, and the part of the word after the word segmentation is marked, and/or, the searched As a result, the word segmentation is performed, and the part of speech of the word after the word segmentation is marked; the similarity calculation module 1218 (corresponding to the filter subunit 1004 in the above embodiment) is set to calculate the similarity between the user input question and the searched problem result, wherein For the calculation algorithm of the specific similarity, refer to the similarity calculation algorithm in the above method embodiment, which is not described here again; the flow programming module 1220 is set to perform process scheduling processing when the problem input by the user is a guided problem, and prompt the user to input relevant guiding information.

It should be noted that each of the above modules may be implemented by software or hardware. For the latter, the foregoing may be implemented by, but not limited to, the foregoing modules are all located in the same processor; or, the modules are located in multiple In the processor.

Embodiments of the present invention also provide a storage medium. Optionally, in the embodiment, the foregoing storage medium may be configured to store program code for performing the following steps:

S1, receiving problem information input through the user terminal;

S2, from a plurality of question and answer libraries, searching for a question and answer library corresponding to the type of the problem information;

S3, searching for an answer corresponding to the problem information from a question and answer library corresponding to the type of the problem information according to a preset rule;

S4. Return the answer corresponding to the problem information to the user terminal as a return result.

Optionally, in this embodiment, the foregoing storage medium may include, but not limited to, a USB flash drive, a Read-Only Memory (ROM), a Random Access Memory (RAM), a mobile hard disk, and a magnetic memory. A variety of media that can store program code, such as a disc or a disc.

For example, the specific examples in this embodiment may refer to the examples described in the foregoing embodiments and the optional embodiments, and details are not described herein again.

It will be apparent to those skilled in the art that the various modules or steps of the present invention described above can be implemented by a general-purpose computing device that can be centralized on a single computing device or distributed across a network of multiple computing devices. Alternatively, they may be implemented by program code executable by the computing device such that they may be stored in the storage device by the computing device and, in some cases, may be different from the order herein. The steps shown or described are performed, or they are separately fabricated into individual integrated circuit modules, or a plurality of modules or steps thereof are fabricated as a single integrated circuit module. Thus, the invention is not limited to any specific combination of hardware and software.

The above description is only the preferred embodiment of the present invention, and is not intended to limit the present invention, and various modifications and changes can be made to the present invention. Any modifications, etc. made within the spirit and principles of the present invention The same substitutions, improvements, and the like are intended to be included in the scope of the present invention.

Industrial applicability

According to the foregoing technical solution provided by the embodiment of the present invention, the problem information input through the user terminal is received; from the plurality of question and answer libraries, the question and answer library corresponding to the type of the problem information is searched; and the information related to the problem is obtained according to the preset rule. The answer corresponding to the question information is searched in the question answering library corresponding to the type; the answer corresponding to the question information is returned as a return result to the user terminal. The question and answer library is divided into multiple question and answer libraries. According to the type of the question information input, the answers corresponding to the question information are searched from the question and answer library corresponding to the type of the question information in the plurality of question and answer libraries, and the intelligence in the related technology is solved. The question and answer system has inflexible semantic support and inconvenient maintenance, which improves the flexibility of semantic support and facilitates the maintenance and update of the intelligent question answering system.

Claims

An intelligent response method, including:

Receiving problem information input through the user terminal;

From a plurality of question and answer libraries, searching for a question and answer library corresponding to the type of the problem information;

Finding an answer corresponding to the problem information from a question and answer library corresponding to the type of the problem information according to a preset rule;

The answer corresponding to the question information is returned to the user terminal as a return result.
The method according to claim 1, wherein the finding an answer corresponding to the question information from a question and answer library corresponding to the type of the question information according to a preset rule comprises:

From the question answering library corresponding to the type of the question information, a question answering library corresponding to the type of the question information according to the problem information and the similarity of the questions stored in the question answering library corresponding to the type of the question information Filtering in the problem;

The filtered answer corresponding to the question is taken as an answer corresponding to the question information.
The method according to claim 2, wherein in the question and answer library corresponding to the type of the problem information, according to the problem information and the degree of similarity of the question stored in the question answering library corresponding to the type of the question information The problem filtering includes:

Obtaining a target problem matching the problem information from a question and answer library corresponding to the type of the problem information;

Obtaining similarity between the problem information and the target problem;

Filtering, in the question and answer library corresponding to the type of the problem information, a target problem whose degree of similarity is less than a preset threshold, and obtaining a first filtering result;

When only one of the target questions is included in the first filtering result, the answer corresponding to the one of the target questions is taken as an answer corresponding to the problem information;

When the plurality of the target questions are included in the first filtering result, an answer corresponding to the target problem having the highest priority among the plurality of the target questions is taken as an answer corresponding to the problem information.
The method according to claim 3, wherein the problem information and the similarity value of the target problem are acquired by at least one of the following:

Mode 1: S=alpha1+beta1*(length2/length1); wherein S represents a similarity value of the problem information and the target problem; length2 is an information length of the problem information and an information length of the target problem Larger, length1 is the information length of the problem information and the information length of the target problem is smaller; both alpha1 and beta1 are real numbers;

Method 2: S=alpha*(Samewords/words1+Samewords/words2)/2+beta*dp*(num1/ Words1+num2/words2); wherein, words1 is the number of words included after the word segmentation of the question information; words2 is the number of words included after the word segmentation of the target question; Samewords is the pair The number of words in the problem information after the word segmentation is included in the segmentation of the target question; num1 is the number of words included in the Samewords that are segmented by the problem information; num2 is included in the Samewords The number of words after the word segmentation of the target question; dp is the minimum value of words1/words2 and words2/words1, and both alpha and beta are real numbers.
The method of claim 4, wherein the mode one is applied to at least one of the following scenarios:

The problem information is the same as the target problem;

The problem information includes the target problem;

The target question contains the problem information.
The method of claim 4, wherein

Obtaining, by the following rules, the number of words included after the word segmentation of the problem information: segmenting the problem information to obtain a plurality of words; assigning weights to each of the words according to the part of speech of each of the words; a number of each of the plurality of words and a weighted sum of each of the words as a number of words included after the word segmentation of the question information;

Obtaining, by the following rules, the number of words included after the segmentation of the target question: segmenting the target question to obtain a plurality of words; assigning weights to each of the words according to the part of speech of each of the words; The number of each of the plurality of words and the weighted sum of each of the words as the number of words included after the word segmentation of the target question.
The method according to any one of claims 1 to 6, wherein from among the plurality of question and answer libraries, finding a question and answer library corresponding to the type of the question information comprises:

Determining whether the problem information is the first type of problem information;

When the problem information is the first type of problem information, acquiring a first type of question answering library corresponding to the first type of problem information;

If the problem information is not the first type of problem information, determining whether the problem information is the second type of problem information;

When the problem information is the second type of problem information, acquiring a second type of question answering library corresponding to the second type of problem information;

Retrieving the problem information from the second type of question and answer library according to the preset rule;

Determining whether the reconfirmed problem information is a third type of problem information;

In the case where the reconfirmed problem information is the third type of question information, a third type of question answering library corresponding to the reconfirmed question information is acquired.
The method according to claim 7, wherein said first type of question information comprises: slang; said first type of question The answer library includes: a slang corpus; wherein the slang corpus stores a slang word and an answer corresponding to the slang word; the second type of problem information includes: specific problem information; the second type of question and answer library The method includes: an equivalent sentence and a standard sentence library; wherein the equivalent sentence and the standard sentence library store the specific question and a standard sentence or an equivalent sentence corresponding to the specific question; the third type of problem information The utility model includes: general problem information; the third type of question answering library includes: a general question answering library, wherein the general question answering library stores an ordinary question and an answer corresponding to the common question.
The method according to claim 7, wherein, from the second type of question and answer library, reconfirming the problem information according to the preset rule comprises:

From the second type of question and answer library, query all questions corresponding to the problem information;

After filtering all the questions according to the preset rule, obtaining a second filtering result;

If the second filtering result is unique, the filtering result is used as the problem information after the reconfirmation;

In the case where the second filtering result does not exist, the problem information input through the user terminal is used as the problem information after the reconfirmation.
The method of claim 7, wherein the method further comprises: before returning the answer corresponding to the question information as a return result to the user terminal, the method further comprising:

Determining whether the answer corresponding to the problem information is the fourth type of problem information; wherein the fourth type of problem information includes: a guided question;

If yes, the display prompt information is triggered, wherein the prompt information is used to prompt to input the guide information corresponding to the fourth type of problem information by using the user terminal;

If not, the answer corresponding to the question information is directly returned to the user terminal as a return result.
An intelligent response device comprising:

a receiving module, configured to receive problem information input through the user terminal;

a first search module, configured to search, from the plurality of question and answer libraries, a question and answer library corresponding to the type of the problem information;

a second searching module, configured to search for an answer corresponding to the problem information from a question and answer library corresponding to the type of the problem information according to a preset rule;

The return module is configured to return an answer corresponding to the question information as a return result to the user terminal.
The apparatus according to claim 11, wherein said second search module is further configured to select a question and answer message corresponding to the type of the question information from the question answering library corresponding to the type of the question information The similarity of the questions stored in the library, filtering the questions in the question answering library corresponding to the type of the problem information; and using the filtered answer corresponding to the question as the answer corresponding to the question information.
The apparatus of claim 12, wherein the second lookup module comprises:

a first obtaining unit, configured to acquire a target problem that matches the problem information from a question and answer library corresponding to the type of the problem information;

a second acquiring unit, configured to acquire a similarity between the problem information and the target problem;

a filtering unit, configured to filter a target problem in which the similarity is less than a preset threshold in a question and answer library corresponding to the type of the problem information, to obtain a first filtering result;

a searching unit, configured to: when the first filtering result includes only one of the target questions, use an answer corresponding to the one of the target questions as an answer corresponding to the problem information; and in the first filtering When the plurality of the target questions are included in the result, an answer corresponding to the target question having the highest priority among the plurality of the target questions is taken as an answer corresponding to the problem information.
The apparatus according to claim 13, wherein the second obtaining unit acquires the similarity value of the problem information and the target question by at least one of the following:

Mode 1: S=alpha1+beta1*(length2/length1); wherein S represents a similarity value of the problem information and the target problem; length2 is an information length of the problem information and an information length of the target problem Larger, length1 is the information length of the problem information and the information length of the target problem is smaller; both alpha1 and beta1 are real numbers;

Method 2: S=alpha*(Samewords/words1+Samewords/words2)/2+beta*dp*(num1/words1+num2/words2); wherein, word1 is the word included after the word segmentation of the problem information Words2 is the number of words included after the word segmentation of the target question; Samewords is the number of the same words included after the word segmentation of the question information is performed after segmentation of the target question; Num1 is the number of words in the Samewords that are segmented by the problem information; num2 is the number of words included in the Samewords for the target problem; dp is words1/words2 and words2/words1 The minimum, alpha and beta are both real numbers.
The apparatus according to any one of claims 11 to 14, wherein the first lookup module comprises:

a first determining unit, configured to determine whether the problem information is the first type of problem information;

a third obtaining unit, configured to acquire a first type of question answering library corresponding to the first type of question information if the problem information is the first type of question information;

a second determining unit, configured to determine whether the problem information is the second type of problem information if the problem information is not the first type of problem information;

a fourth obtaining unit, configured to acquire a second type of question answering library corresponding to the second type of question information if the problem information is the second type of question information;

a confirmation unit, configured to re-confirm the problem letter according to the preset rule from the second type of question and answer library interest;

a third determining unit, configured to determine whether the reconfirmed problem information is a third type of problem information;

The fifth obtaining unit is configured to acquire a third type of question answering library corresponding to the reconfirmed question information if the reconfirmed question information is the third type of question information.
The apparatus of claim 15, wherein the confirmation unit comprises:

Querying a subunit, configured to query all questions corresponding to the problem information from the second type of question and answer library;

a filtering subunit, configured to filter all the questions according to the preset rule to obtain a second filtering result;

a confirmation subunit, configured to use the filtering result as the problem information after the reconfirmation when the second filtering result is unique; and in the case where the second filtering result does not exist, The problem information input by the user terminal is used as the problem information after the reconfirmation.
The device according to claim 15, wherein the device further comprises: a determining module, configured to determine whether the answer corresponding to the problem information is the fourth type of problem information; wherein the fourth type of problem information comprises: a display module, configured to trigger display of the prompt information when the answer corresponding to the problem information is the fourth type of question information, wherein the prompt information is used to prompt input and the first Guidance information corresponding to the four types of problem information;

The returning module is further configured to directly return an answer corresponding to the question information as a return result to the user terminal if the answer corresponding to the question information is not the fourth type of question information.