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Information recommendation method and system based on knowledge graph and graph convolutional network

A knowledge graph and convolutional network technology, applied in the field of natural language processing, can solve the problems that the recommendation information is difficult to accurately match the user's needs, and the accuracy of the graph node feature representation is insufficient, so as to improve the accuracy and ensure the accuracy.

Pending Publication Date: 2021-05-07
CHONGQING MEGALIGHT TECH CO LTD
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  • Claims
  • Application Information

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Problems solved by technology

[0003] In view of the problems existing in the above existing technologies, the present invention proposes an information recommendation method and system based on knowledge graphs and graph convolutional networks, which mainly solves the problem that the recommendation information is difficult to accurately match user needs due to insufficient accuracy of graph node feature representation in the prior art The problem

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  • Information recommendation method and system based on knowledge graph and graph convolutional network
  • Information recommendation method and system based on knowledge graph and graph convolutional network
  • Information recommendation method and system based on knowledge graph and graph convolutional network

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[0034] Embodiments of the present invention are described below through specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific implementation modes, and various modifications or changes can be made to the details in this specification based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that, in the case of no conflict, the following embodiments and features in the embodiments can be combined with each other.

[0035] It should be noted that the diagrams provided in the following embodiments are only schematically illustrating the basic ideas of the present invention, and only the components related to the present invention are shown in the diagrams rather than the number, shape and shape of the compo...

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Abstract

The invention provides an information recommendation method and system based on a knowledge graph and a graph convolutional network, and the method comprises the steps: constructing a user-article interaction graph according to the interaction information of a user and an article; according to the attribute information of the article, constructing an article-attribute knowledge graph; according to the user-article interaction graph and the article-attribute knowledge graph, constructing a triple knowledge graph taking the user, the article and the attribute as entities; obtaining a feature representation of each entity in the triple knowledge graph and an adjacent node feature representation of the corresponding entity, and carrying out clustering through a graph convolutional network to obtain one or more recommendation results. The accuracy of information recommendation can be effectively improved.

Description

technical field [0001] The present invention relates to the field of natural language processing, in particular to an information recommendation method and system based on a knowledge map and a graph convolutional network. Background technique [0002] The recommendation system is a common application of natural language processing (NLP) methods, and has been practiced in real life. The rapid development of recommender systems has made it very popular in web applications such as search engines, e-commerce, social media sites, and news portals, and almost every service that provides content to users is equipped with recommender systems. In order to predict user preferences from key and widely available user behavior data (such as interaction data), traditional research mostly uses collaborative filtering (CF) methods. Despite its effectiveness and generality, the CF method cannot model side information (such as attributes of items, relations of users, etc.), and thus perform...

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Application Information

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IPC IPC(8): G06F16/9536G06F16/36G06F16/906G06N3/04
CPCG06F16/9536G06F16/367G06F16/906G06N3/045
Inventor 彭德光
Owner CHONGQING MEGALIGHT TECH CO LTD