Knowledge graph-based question and answer intention identification method

A recognition method and knowledge map technology, applied in the direction of neural learning methods, instruments, semantic tool creation, etc., can solve the problems of labor-intensive, manual classification and labeling, poor scalability, etc., and achieve the effect of meeting various needs

Pending Publication Date: 2020-06-16
TONGFANG KNOWLEDGE NETWORK TECH CO LTD (BEIJING) +1
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AI Technical Summary

Problems solved by technology

[0003] Traditional intent recognition mainly uses syntax and semantic analysis, syntax dependency analysis, and template matching methods. This method requires a large number of rules to support, and the recognition accuracy is high within the specified range, but the scalability is poor. Once the rules change Reconfiguration is required, which...

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  • Knowledge graph-based question and answer intention identification method
  • Knowledge graph-based question and answer intention identification method
  • Knowledge graph-based question and answer intention identification method

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Embodiment Construction

[0020] In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be described in further detail below with reference to the embodiments and accompanying drawings.

[0021] like figure 1 As shown in the figure, it is a method flow of question answering intent recognition based on knowledge graph, including the following steps:

[0022] Step 10 constructs a domain subject dictionary;

[0023] Since there are many professional vocabulary, entity names and abbreviations in different professional fields, it is necessary to organize the relevant topic dictionaries in the field of vocabulary construction in advance to assist in intent recognition. In many researches on intent recognition, there is a lack of topic dictionary construction in the professional field. It is believed that this method lacks flexibility and requires manual maintenance. However, in the application scenario where users need to search accur...

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Abstract

The invention discloses a knowledge graph-based question and answer intention recognition method. The method comprises the steps of constructing a domain topic dictionary; constructing a template; performing part-of-speech analysis and syntactic dependency analysis on the retrieval statement; calculating the similarity between the search text and the template sample by utilizing the word vector and an LDA algorithm; on the basis of a known word vector, carrying out wider intention recognition on the basis of TextCNN to serve as a result of open information; extracting keywords from the domainmap. According to the method, intention recognition is achieved by integrating multiple methods, comprehensive retrieval of accurate answers and related information is achieved in combination with theknowledge graph of the field, and various requirements of users are met.

Description

technical field [0001] The invention relates to the technical fields of natural language processing and deep learning, and in particular, to a question-and-answer intent recognition method based on a knowledge graph. Background technique [0002] With the explosive growth of contemporary information and the rapid development of science and technology, people are no longer satisfied with the function of search engines and are no longer satisfied with the traditional mode of returning a large number of web pages or links containing relevant keywords after entering keywords in search engines. In this case, the user also needs to manually distinguish and browse in the returned results, and the redundant results often need to waste a lot of time of the user to eliminate, and the accuracy is not high. More easy-to-use search engines allow users to obtain more directional answers or related knowledge after inputting colloquial description information, which requires programs to ana...

Claims

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Application Information

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IPC IPC(8): G06F16/33G06F16/332G06F16/35G06F16/36G06N3/04G06N3/08
CPCG06F16/3329G06F16/3335G06F16/3344G06F16/35G06F16/367G06F16/374G06N3/08G06N3/045
Inventor 冯淑雯段飞虎谭超冯自强李云鹏张宏伟
Owner TONGFANG KNOWLEDGE NETWORK TECH CO LTD (BEIJING)
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