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Method and device for knowledge map prediction

A knowledge map and entity technology, applied in the field of knowledge map prediction, can solve problems such as data sparseness

Active Publication Date: 2021-05-11
BEIJING UNIV OF POSTS & TELECOMM +1
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  • Summary
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Problems solved by technology

However, the TransE model faces the problem of data sparsity when learning entity and relation vectors

Method used

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  • Method and device for knowledge map prediction
  • Method and device for knowledge map prediction
  • Method and device for knowledge map prediction

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Embodiment Construction

[0073] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts shall fall within the protection scope of the present invention.

[0074] The TransE model regards the relationship in the knowledge graph as a translational transformation between entity vectors in a low-dimensional space. In the embodiment of the present invention, a triple can be expressed as (h, l, t), where h represents a left entity, l represents a relationship, and t represents a right entity. By constantly adjusting the vectors of the left entity, relationship and right entity in each triple instance, the sum of t...

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Abstract

Embodiments of the present invention provide a method and device for knowledge map prediction, including: acquiring a first entity and a second entity; establishing a first triangular subgraph according to the first entity and the second entity; The first triangular subgraph and embedded model determine the relationship between the first entity and the second entity. The embodiment of the present invention obtains the first entity and the second entity, and establishes a triangular subgraph containing the first entity and the second entity, and determines the relationship between the first entity and the second entity according to the triangular subgraph and the embedded model. Relationship. The embodiment of the present invention can make full use of the relationship types of the triangular subgraph in the knowledge graph at the semantic level to obtain the correlation between object entities, thereby avoiding the problem of data sparseness caused by only considering the direct semantic correlation of entity pairs.

Description

technical field [0001] The present invention relates to the computer field, and more specifically, to a method and device for knowledge map prediction in the computer field. Background technique [0002] Knowledge graphs aim to describe various entities or concepts and their relationships that exist in the real world, and are generally represented by triples, which include left entities, right entities, and relationships. The knowledge graph can also be viewed as a huge graph, where nodes represent entities or concepts, and edges are composed of attributes or relationships. In addition to providing users with links related to query words, the knowledge graph also endows query words with richer semantic information and provides more accurate and direct answers related to query words. [0003] Traditional search engines often can only provide users with web pages related to query words for users to choose by themselves. By utilizing the structured entity knowledge of the kno...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F16/36G06F17/15
CPCG06F17/15G06Q10/04G06F16/951
Inventor 刘志容高升何秀强
Owner BEIJING UNIV OF POSTS & TELECOMM
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