Knowledge graph vector representation generation method, device and equipment

A technology of knowledge graph and vector representation, which is applied in the fields of computer and artificial intelligence, can solve problems such as the need to improve accuracy and limited representation ability, and achieve the effects of improving modeling ability, sufficient representation ability, and improving accuracy

Active Publication Date: 2020-02-14
BEIJING BAIDU NETCOM SCI & TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] Knowledge map representation learning in related technologies learns static and fixed vector representations for map elements (including entities and relationships), but the representation ability is limited and the accuracy needs to be improved

Method used

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  • Knowledge graph vector representation generation method, device and equipment
  • Knowledge graph vector representation generation method, device and equipment
  • Knowledge graph vector representation generation method, device and equipment

Examples

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Embodiment Construction

[0035] Exemplary embodiments of the present application are described below in conjunction with the accompanying drawings, which include various details of the embodiments of the present application to facilitate understanding, and they should be regarded as exemplary only. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the application. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.

[0036] figure 1 A schematic flowchart of a method for generating a vector representation of a knowledge graph provided in the embodiment of the present application, as shown in figure 1 As shown, the method includes:

[0037] Step 101, acquire a knowledge graph, where the knowledge graph includes multiple entity nodes.

[0038] In practical applications, when perf...

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Abstract

The invention provides a knowledge graph vector representation generation method, device and equipment, and relates to the technical field of artificial intelligence, and the specific implementation scheme is that the method comprises the steps: obtaining a knowledge graph, and enabling the knowledge graph to comprise a plurality of entity nodes; obtaining a context type and context data corresponding to the knowledge graph; and generating vector representations corresponding to the plurality of entity nodes through a context model according to the context data and the context type. Therefore,finer semantic representation of the entity in the context is realized, and the knowledge graph representation learning accuracy is further improved.

Description

technical field [0001] The present application relates to the field of computer technology, in particular to the field of artificial intelligence technology, and proposes a method, device and equipment for generating vector representations of knowledge graphs. Background technique [0002] The knowledge map is a directed graph structure knowledge base that describes the real knowledge of the world. The goal of knowledge map representation learning is to represent the entities / relationships of discrete symbols in the knowledge map as vectors: on the one hand, the vector representation can retain the structural aspects of entities in the knowledge map On the other hand, it facilitates the use of knowledge graphs for application tasks. At present, in tasks such as information extraction, question answering, and reading comprehension, knowledge graphs are applied and function in the form of vectors. [0003] Knowledge map representation learning in related technologies learns s...

Claims

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Application Information

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IPC IPC(8): G06F16/36G06F16/31
CPCG06F16/367G06F16/31G06F40/279G06F16/9024G06F16/9017G06N5/022G06N3/08G06N3/042G06N3/045G06F16/316G06F16/35G06F16/906G06F16/36G06F16/3347G06N5/02
Inventor 王泉黄苹苹王海峰姜文斌吕雅娟朱勇吴华
Owner BEIJING BAIDU NETCOM SCI & TECH CO LTD
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