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Knowledge map distributed representation method capable of encoding relational semantic diversity structure

A knowledge graph and distributed technology, applied in the field of data storage and processing, can solve the problems of failure to consider the diversity of graph structure and cannot handle it well, and achieve good practical value, strong scalability, good completion and prediction effect of effect

Active Publication Date: 2018-12-21
ZHEJIANG UNIV
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  • Abstract
  • Description
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  • Application Information

AI Technical Summary

Problems solved by technology

However, the existing distributed representation methods for knowledge graphs fail to consider the diversity of graph structures, so they cannot handle these diverse relational semantics well.

Method used

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  • Knowledge map distributed representation method capable of encoding relational semantic diversity structure
  • Knowledge map distributed representation method capable of encoding relational semantic diversity structure
  • Knowledge map distributed representation method capable of encoding relational semantic diversity structure

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Embodiment Construction

[0023] In order to describe the present invention more specifically, the technical solutions of the present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0024] The present invention proposes a knowledge map distributed representation method capable of encoding relational semantic diversity structures, including the following steps:

[0025] (1) Obtain all triples (h, r, t) in the knowledge graph, h is the head entity, r is the relationship, and t is the tail entity; for any triplet (h, r, t), calculate the Confidence s(h,r,t) for triplet (h,r,t).

[0026] The present invention calculates the probability that the input triplet (h, r, t) is true by defining an evaluation function, that is, the confidence degree s(h, r, t). The probability evaluation function includes two parts: a joint operator and a similarity calculation sub, by defining a linear transformation matrix in the joint operator for each relat...

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Abstract

The invention discloses a knowledge map distributed representation method capable of encoding relationship semantic diversity structure, From the point of view of graph structure diversity in knowledge map, mining and summarizing the subgraph structure which contains abundant semantic information, and connecting the subgraph structure with the related semantic information, such as reflexivity, symmetry, transitivity and so on; The method of the invention can better encode the diversity of the graph structure, Therefore, it can better capture the semantic information in the knowledge map, achieve better completion and prediction effect, achieve better performance in the link prediction task, and has a strong scalability, which has a good practical value for the application of the semantic diversity structure of encoding relations in the distributed representation of the knowledge map.

Description

technical field [0001] The invention belongs to the technical field of data storage and processing, and in particular relates to a knowledge graph distributed representation method capable of encoding relational semantic diversity structures. Background technique [0002] In recent years, the knowledge graph has received great attention from the industry, and has been successfully applied in many fields, such as search engines, intelligent customer service, voice robots, etc. Many large-scale knowledge graphs have been gradually built, such as Google Knowledge Graph and the open Freebase , Yago, etc. The knowledge graph mainly includes entities, relationships, and triples. Each triple represents a piece of knowledge, that is, there is a certain relationship between two entities, represented by (h, r, t), where h and t represent the head respectively. Entity and tail entity, r represents the relationship, for example (Hangzhou, located in the country, China) means a piece of...

Claims

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Application Information

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IPC IPC(8): G06F17/30
Inventor 陈华钧张文张宇轩
Owner ZHEJIANG UNIV
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