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Knowledge graph-based edge relationship prediction method, apparatus and device, and storage medium

A technology of knowledge graph and relationship, which is applied in the field of edge relationship prediction method, device, equipment and storage medium based on knowledge graph. The effects of comprehensive information, improved accuracy, and improved completeness

Pending Publication Date: 2021-03-19
BEIJING BAIDU NETCOM SCI & TECH CO LTD
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  • Abstract
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  • Claims
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AI Technical Summary

Problems solved by technology

However, the current construction cost of knowledge graphs in professional fields is high and its completeness is difficult to guarantee, resulting in low accuracy of knowledge reasoning calculations

Method used

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  • Knowledge graph-based edge relationship prediction method, apparatus and device, and storage medium
  • Knowledge graph-based edge relationship prediction method, apparatus and device, and storage medium
  • Knowledge graph-based edge relationship prediction method, apparatus and device, and storage medium

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Embodiment Construction

[0030] 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.

[0031] figure 1 It shows a flow chart of a knowledge graph-based edge relationship prediction method based on a knowledge graph provided by an embodiment of the present application. The method includes:

[0032] S101. Obtain a first knowledge map, where the first knowledge map is constructed based on structured data and unstructured data in a target knowledge domain...

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Abstract

The invention discloses an edge relationship prediction method and device based on a knowledge graph, equipment and a storage medium, and relates to the technical field of deep learning and the technical field of knowledge graphs. The method comprises the steps of obtaining a first knowledge graph, wherein the first knowledge graph is constructed based on structured data and unstructured data of atarget knowledge domain; obtaining a first knowledge representation model, wherein the first knowledge representation model is generated by training a first BERT model through the corpus data set ofthe target knowledge domain; and inputting the marking word vectors and the position word vectors of the plurality of nodes of the first knowledge graph into a second BERT model for information aggregation processing to obtain edge relationship information between the plurality of nodes of the first knowledge graph and respective neighbor nodes. By utilizing the embodiment of the invention, the edge relationship information among the nodes in the knowledge graph can be obtained.

Description

technical field [0001] The present application relates to the technical field of deep learning and the technical field of knowledge graph, and specifically relates to a method, device, equipment and storage medium for edge relationship prediction based on knowledge graph. Background technique [0002] Knowledge Graph usually refers to a semantic network that can reveal the relationship between entities. It is based on data mining, information processing, graphics drawing, etc., and uses visual graphs to visualize complex knowledge fields. It can be used to a certain extent. It embodies the law of development in the field of knowledge. Knowledge representation is a description of knowledge, which includes a computer-acceptable data structure for describing knowledge. Knowledge Inference (Knowledge Inference) usually refers to the process of simulating human intelligent reasoning in a computer or intelligent system, and using formalized knowledge to carry out machine thinking...

Claims

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Application Information

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IPC IPC(8): G06F16/36G06N5/04
CPCG06F16/367G06N5/04
Inventor 张峥郑宇宏徐伟建罗雨
Owner BEIJING BAIDU NETCOM SCI & TECH CO LTD
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