Tripartite graph random walk recommendation method based on word2vec label similarity

Abstract

The invention discloses a tripartite graph random walk recommendation method based on word2vec label similarity. The tripartite graph random walk recommendation method comprises the steps that S1, thesimilarity between articles is calculated based on an ICF algorithm-cosRA; S2, generating a recommendation list according to the similarity of the articles and the historical behaviors of the user; S3, constructing a user-article bipartite graph according to the target user and the recommendation list, and establishing a tripartite graph model based on introduction of label nodes into the user-article bipartite graph; S4, constructing a word2vec model, and taking the number memory vocabularies as a corpus for training the word2vec; S5, endowing the weight of the edge between the article labels in the tripartite graph; S6, random walk is carried out on the tripartite graph from the user node, after several times of random walk, the probability that each article node is accessed can converge to one number, and the access probability is the weight of the articles in the final recommendation list.

Description

technical field [0001] The invention belongs to the technical field of Internet information recommendation, and in particular relates to a three-part graph random walk recommendation method based on word2vec tag similarity. Background technique [0002] With the development of information technology and the Internet, people have gradually entered an era of information overload from an era of information scarcity. In this era, both information consumers and information producers have encountered great challenges: as an information consumer, it is very difficult to find the information they are interested in from a large amount of information; as an information producer, How to make the information produced by oneself stand out and attract the attention of the majority of users is also a very difficult thing. The recommendation system is an important tool to solve this contradiction. The task of the recommendation system is to connect users and information. On the one hand, ...

AI Technical Summary

Problems solved by technology

[0013] The purpose of the present invention is to address the above-mentioned deficiencies in the prior art, to provide a three-part graph random walk recommendation method based on word2vec label similarity, to solve the problem that the traditional algorithm leads to a large difference between the items recommended to the user and the actual needs of the user , which reduces the user's sense of experience

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