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Question-answering method based on knowledge graph completion

A knowledge map and completion technology, applied in the field of question answering based on knowledge map completion, can solve problems such as missing relationships and low precision

Active Publication Date: 2020-12-01
CHONGQING UNIV OF POSTS & TELECOMM
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

This invention solves the problem of lack of relationship in KGs, alleviates the low-precision problem of Question answering over Knowledge Graphs (KGs-QA) based on knowledge graphs, and improves the application of intelligent QA based on KGs

Method used

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  • Question-answering method based on knowledge graph completion

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Embodiment Construction

[0078] Embodiments of the present invention are described below through specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific implementation modes, and various modifications or changes can be made to the details in this specification based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the diagrams provided in the following embodiments are only schematically illustrating the basic concept of the present invention, and the following embodiments and the features in the embodiments can be combined with each other in the case of no conflict.

[0079] Wherein, the accompanying drawings are for illustrative purposes only, and represent only schematic diagrams, rather than physical drawings, and should...

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Abstract

The invention relates to a question-answering method based on knowledge graph completion, and belongs to the field of natural language processing, and the method comprises the following steps: S1, dividing input Q into words or phrases; s2, representing the words as vectors by using a word vector model BERT to obtain a matrix as model input; s3, identifying entities in the Q by using an entity identification technology to obtain a candidate entity set; s4, querying the category of the eKGs, and replacing the entities in the Q with c; s5, constructing a declarative query cyber, and obtaining acandidate triple set so as to obtain a candidate relationship set; s6, linking based on the relationship between Qc and rij; s7, in the KGs, if the relationship between the eKGs and the rij is absent;s8, learning new vector representation of entities eKGs and entities in neighborhoods of the eKGs; s9, estimating the importance of entities in the neighborhood of the central entity; s10, executingrelation prediction on the basis of existing related triples; and S11, obtaining an answer A based on knowledge graph reasoning of entities and relationships.

Description

technical field [0001] The invention belongs to the field of natural language processing and relates to a question answering method based on knowledge graph completion. Background technique [0002] In recent years, the rapid development of artificial intelligence technology has gradually become a hot spot of social concern. With the rapid development of artificial intelligence technology and the explosive growth of network information, the storage and representation of knowledge has become particularly important. Knowledge graphs (Knowledge Graphs, KGs) are one of the most effective ways to represent knowledge. It extracts knowledge from massive network information and organizes it into structured data in the form of triples, which is convenient for efficient computer processing. As Google uses KGs in its search engine, intelligent question answering (QA) has also begun to use KGs on a large scale. With the development of intelligent applications, the lack of a large numb...

Claims

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Application Information

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IPC IPC(8): G06F16/33G06F16/332G06F16/36G06F40/295G06F40/30G06N3/04G06N3/08
CPCG06F16/3329G06F16/3344G06F16/367G06F40/295G06F40/30G06N3/08G06N3/047G06N3/048G06N3/045
Inventor 赵芬李银国李俊王新恒
Owner CHONGQING UNIV OF POSTS & TELECOMM
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