Knowledge graph intelligent question-answering method based on relationship 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, and can solve problems that are difficult to meet people's needs

Active Publication Date: 2020-10-16
CHONGQING UNIV OF POSTS & TELECOMM
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  • Application Information

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Problems solved by technology

[0002] The keyword-based search method of traditional search engines lacks semantic analysis and sema

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  • Knowledge graph intelligent question-answering method based on relationship prediction
  • Knowledge graph intelligent question-answering method based on relationship prediction
  • Knowledge graph intelligent question-answering method based on relationship prediction

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Embodiment Construction

[0036] 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 embodiments, 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.

[0037] Wherein, the accompanying drawings are for illustrative purposes only, and represent only schematic diagrams, rather than physical drawings, and should not be c...

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Abstract

The invention relates to a knowledge graph intelligent question-answering method based on relation prediction, and belongs to the field of natural language processing. The method comprises the following steps: S1, inputting a problem Q, and preprocessing the problem; S2, identifying an entity equalization in the problem by utilizing an entity identification technology, and mapping the entity equalization to a corresponding entity eKGs in the KGs; S3, querying the category c of the entity eKGs in the KGs, replacing the entity equest in the problem Q with the category c, and marking the categoryc as Qc; S4, mapping a relationship r from the Qc; S5, in the KGs, if there is no relation between the entity eKGs and the relation r; S6, learning new vector representation of the center entity eKGs; S7, deducing a hidden relationship in the KGs based on the existing related triples; and S8, obtaining an answer A based on knowledge graph reasoning of entities and relationships. According to themethod, the corresponding relation between the question entity and the knowledge graph entity and the corresponding relation between the question natural language description and the knowledge graph semantic relation can be found.

Description

technical field [0001] The invention belongs to the field of natural language processing, and relates to a knowledge map 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, which has become increasingly difficult to meet people's needs. For users, the interaction mode that conforms to the expression of human natural language is the best. When the question answering system shows enough intelligence, it can meet the needs of users for this interaction mode. Google proposed the concept of Knowledge Graphs (KGs) in 2012 to further promote 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 amount of real...

Claims

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Application Information

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IPC IPC(8): G06F16/33G06F16/332G06F16/36G06F16/35G06F40/295G06F40/30
CPCG06F16/3329G06F16/3344G06F16/367G06F16/35G06F40/295G06F40/30
Inventor 赵芬李银国侯杰李俊王新恒
Owner CHONGQING UNIV OF POSTS & TELECOMM
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