Domain question and answer-oriented knowledge graph construction method

A knowledge graph and construction method technology, applied in natural language processing, knowledge graph construction, professional field question answering, can solve problems such as low answer accuracy, improve user experience, high entity relevance, simple and accurate answer search strategy Effect

Pending Publication Date: 2021-01-01
SOUTH CHINA UNIV OF TECH
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AI Technical Summary

Problems solved by technology

[0007] In view of the fact that the professional words of the existing domain-type question-and-answer are difficult to semanticize and the accuracy of the answer is low, the present invention mainly uses the strong correlation between the nodes of the knowledge map to formulate different cate

Method used

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Embodiment Construction

[0051] In order to make the purpose, technical solution and advantages of the present invention more clear and definite, the present invention will be further described in detail below with reference to the accompanying drawings and examples.

[0052] like figure 1 , figure 2 As shown, a knowledge map construction method for domain question answering, including the following steps:

[0053] The first step is to collect the frequently asked questions and their answers in the targeted fields, classify the answers to these questions according to the requirements, and store them in relational databases such as MySQL; among them, the number of questions in different categories is 1:1, which is convenient for balancing the model tendency. This step is to obtain the specific label of the problem and classify the collection problem;

[0054] The collected data is stored in the form of triplets, data format: . The classification categories are further divided according to the need...

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Abstract

The invention provides a domain question and answer-oriented knowledge graph construction method, which comprises the following steps: S1, collecting common questions and answers of a user to a domainon the basis of the professional domain, classifying the questions to form a question set, and training a Chinese pre-training classification model on the basis of the data; s2, performing word segmentation and part-of-speech tagging classification on each question in the question set by using the question set in the step S1, constructing a knowledge graph of the current classification by using aword dictionary obtained after each question formed by the same category is subjected to word segmentation and part-of-speech tagging, and storing the knowledge graph in a graph database; s3, performing sub-category division on the user problems according to actual requirements, performing retrieval on retrieval rules used in the knowledge graph of the corresponding category in the graph databaseaccording to sub-category results and the keyword set, and obtaining retrieval labels; and S4, retrieving corresponding labels, extracting questions represented by the labels in the database, and returning answers corresponding to the questions to the user.

Description

technical field [0001] The invention relates to the fields of natural language processing, knowledge map construction, and professional field question answering, and in particular to a method for building knowledge map oriented to field question answering. Background technique [0002] The main purpose of domain-based question answering systems is different from general-purpose question-answering systems. It is mainly to answer professional questions in related professional fields for users. Usually, professional fields involve many proprietary words, and conventional question-answering methods cannot understand the semantic associations of these proprietary words. At the same time, the traditional question-and-answer method has insufficient relevance of proprietary words, resulting in inaccurate answers and other problems. [0003] Therefore, by analyzing the collected questions and answers frequently asked by users in the field through natural language processing methods, ...

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Application Information

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IPC IPC(8): G06F16/332G06F16/35G06F40/289
CPCG06F16/3329G06F16/35G06F40/289
Inventor 黄翰陈芳宇李刚徐杨郝志峰
Owner SOUTH CHINA UNIV OF TECH
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