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Bilinear graph network recommendation method and system based on knowledge graph enhancement

A technology of knowledge graph and recommendation method, applied in the field of bilinear graph network recommendation, which can solve problems such as poor applicability and accuracy

Active Publication Date: 2021-03-26
XIDIAN UNIV
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Problems solved by technology

[0006] The purpose of the present invention is to provide a bilinear graph network recommendation method and system based on knowledge map enhancement to solve the problems of poor applicability and accuracy in the network recommendation method in the prior art

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  • Bilinear graph network recommendation method and system based on knowledge graph enhancement
  • Bilinear graph network recommendation method and system based on knowledge graph enhancement
  • Bilinear graph network recommendation method and system based on knowledge graph enhancement

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Embodiment Construction

[0100] The purpose of the present invention is to provide a bilinear graph network recommendation method and system based on knowledge graph enhancement to solve the problems of poor applicability and accuracy in network recommendation methods in the prior art.

[0101] Method example:

[0102] A bilinear graph network recommendation method based on knowledge graph enhancement, the process is as follows figure 1 shown, including the following steps:

[0103] Step 1: Construct the user feedback bidirectional graph based on the interaction data between the user and the item, construct the knowledge graph of the item according to the attribute characteristics of the item, and initialize the user node representation vector, the item node representation vector and the entity node representation vector.

[0104] Step 2: Input the initialized user node representation vector, item node representation vector and entity node representation vector into the bilinear graph network aggrega...

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Abstract

The invention provides a bilinear graph network recommendation method and system based on knowledge graph enhancement, and the method comprises the steps: constructing a user feedback bigraph according to the interaction data of a user and an article, and constructing a knowledge graph of the article according to the attribute features of the article; inputting the initialized user node representation vector, article node representation vector and entity node representation vector into a bilinear graph network aggregation layer, and updating the user node representation vector, article node representation vector and entity node representation vector for the first time; updating the user node representation vector, the article node representation vector and the entity node representation vector for at least one time; and cascading the user node representation vectors and the article node representation vectors updated each time, calculating the inner product of the vectors, and judgingwhether to recommend the article to the user or not according to the calculated inner product. According to the technical scheme provided by the invention, the applicability and accuracy of the network recommendation method can be improved.

Description

technical field [0001] The invention belongs to the field of network recommendation, and in particular relates to a bilinear graph network recommendation method and system based on knowledge map enhancement. Background technique [0002] With the development of the times, it has become a common shopping method to choose the goods you need through the Internet. Various commodities and services on online shopping platforms have greatly enriched people's lives, but they have also created the problem of "information overload". How consumers can choose the commodities that suit them in the shortest time has become a difficult problem. [0003] The emergence of information recommendation technology has solved the above-mentioned technical problems well. As one of the technical means to solve the problem of information overload, information recommendation technology has great significance and value in both theory and application. Theoretically speaking, the information recommenda...

Claims

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Application Information

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IPC IPC(8): G06F16/9535G06F16/36
CPCG06F16/9535G06F16/367
Inventor 宋彬许龙涛郭洁
Owner XIDIAN UNIV
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