A Knowledge Graph Intelligent Question Answering Method Based on Relation Prediction

A technology of knowledge graph and intelligent question answering, which is applied in the field of knowledge graph intelligent question answering based on relationship prediction, which can solve problems such as difficulty in meeting people's needs.
CN111782769BActive Publication Date: 2022-07-08CHONGQING UNIV OF POSTS & TELECOMM
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Patent Information

Authority / Receiving Office
CN Β· China
Patent Type
Patents(China)
Current Assignee / Owner
CHONGQING UNIV OF POSTS & TELECOMM
Publication Date
2022-07-08

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Abstract

The invention relates to a knowledge graph intelligent question answering method based on relationship prediction, and belongs to the field of natural language processing. The method includes the steps: S1: input the question Q, and preprocess the question; S2: identify the entity e in the question by using entity recognition technology question , and converts the entity e question Map to the corresponding entity e in KGs KGs ;S3: Query entity e in KGs KGs of category c, replace entity e in question Q with category c question , marked as Q c ;S4: from Q c Map out the relation r in ; S5: In KGs, if the entity e KGs Missing connection with relation r; S6: learning center entity e KGs A new vector representation of ; S7: Infer hidden relations in KGs based on existing related triples; S8: Knowledge graph reasoning based on entities and relations, get answer A. The invention can find the corresponding relationship of "question sentence entity--knowledge graph entity", and the corresponding relationship of "question sentence natural language description-knowledge graph semantic relationship".
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Description

technical field

[0001] The invention belongs to the field of natural language processing, and relates to a knowledge graph intelligent question answering method based on relationship prediction. Background technique

[0002] The keyword-based search method of traditional search engines lacks semantic analysis and semantic understanding of natural language, making it increasingly difficult to meet people's needs. For users, the best interaction method is in line with human natural language expression. When the question answering system exhibits sufficient intelligence, it can meet the user's needs for this interaction method. In 2012, Google proposed the concept of Knowledge Graphs (KGs), which further promoted the question answering system in the direction of intelligence. With the development of knowledge graph technology, intelligent question answering system has shown new development prospects. The rise of social networking sites has provided a large number of real ques...

Claims

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