Intelligent question-answering method and device based on knowledge graph

Abstract

The embodiment of the invention provides an intelligent question-answering method and device based on a knowledge graph. The intelligent question-answering method comprises the steps: receiving a userquestion transmitted by a client, and respectively carrying out the entity recognition and intention recognition; and generating a knowledge graph query statement according to the entity identification result and the intention identification result, searching in a knowledge graph database to obtain an answer corresponding to the user question, and returning the answer to the client, wherein the knowledge graph database comprises entity names, entity attribute information and entity relationship information. The intelligent question-answering method and device based on a knowledge graph generates knowledge graph query statement after entity identification and intention identification are carried out based on a user question, and carries out searching in the knowledge graph database containing the entity name, the entity attribute information and the entity relation information to obtain the answer corresponding to the user question and return the answer to the client, thus achieving intelligent automatic answering of the user question, and improving the answering efficiency and accuracy.

Description

technical field [0001] The invention relates to the field of computer technology, in particular to an intelligent question answering method and device based on a knowledge map. Background technique [0002] With the popularization of Internet applications, countless patients seek answers to user questions related to diseases on the Internet every day. However, traditional question-answering systems or search engines often retrieve not the information users want, but only based on the key points. There are thousands of related links retrieved by word search, and patients have to find the answers they want in the massive related links. When there are no relevant answers in these links, patients often go to some doctor question-and-answer communities to find professional doctors to ask questions. Since most of the user questions of patients are repetitive knowledge user questions, it is inevitable that doctors will repeat their work and the efficiency is low. Correspondingly, ...

AI Technical Summary

Problems solved by technology

When there are no relevant answers in these links, patients often go to some doctor question-and-answer communities to find professional doctors to ask questions. Since most of the user questions of patients are repetitive knowledge user questions, it is inevitable that doctors will repeat their work and the efficiency is low. Correspondingly, it also affects the efficiency of patients to obtain answers to user questions

In addition, due to the different levels of doctors, the answers given by different doctors may also be different. Therefore, it is often difficult for patients to determine the accuracy of the answers to user questions.

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