Knowledge base question-answering method based on deep learning

Abstract

The invention discloses a knowledge base questioning and answering method based on deep learning, and the method comprises the following steps: performing theme entity identification on natural language questions of a user to identify a plurality of theme entities; performing weight assignment according to the plurality of theme entities to obtain a plurality of central entities with different weights; selecting candidate answer paths according to the plurality of central entities with different weights, and calculating a similarity total score; sorting and weighting the candidate answer pathsaccording to the similarity total score to obtain a plurality of candidate answer paths with different weights; and performing function matching calculation on the plurality of central entities withdifferent weights and the plurality of candidate answer paths with different weights to obtain a final answer, and feeding back the final answer to the user. According to the method, the problem thata traditional question-answering method identifies wrong theme entities or cannot identify theme entities is solved, the error rate of a theme entity identification model is reduced, the accuracy of an attribute relationship detection model is improved, and the question-answering accuracy of a whole knowledge base is improved.

Description

technical field [0001] The present invention relates to the technical field of computer question answering systems, in particular to a knowledge base question answering method based on deep learning. Background technique [0002] In recent years, with the continuous innovation of science and technology, artificial intelligence has also achieved rapid development. As an important branch of artificial intelligence, automatic question answering system has also received more and more attention. The exponential growth of network information has become an inevitable trend of Internet development. Facing the growth of such a huge amount of information, how to quickly extract the effective information needed by users will become very important. The emergence of search engine technology largely meets people's needs for information acquisition. Search engines have gradually become a convenient way for people to acquire knowledge and filter information. However, traditional search ...

AI Technical Summary

Problems solved by technology

This method aims to solve the problem that the traditional question and answer method identifies the wrong subject entity or cannot identify the subject entity, reduces the error rate of the subject entity recognition model, improves the accuracy of the attribute relationship detection model, and improves the accuracy of the entire knowledge base question answering

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