Method for realizing fashion suit recommendation through graph neural network

Abstract

The invention discloses a method for realizing fashion suit recommendation through a graph neural network, and the method comprises the steps: constructing a network structure comprising a user node,a suit node and a single-item node, initializing the vector representation of each node, and constructing the relation between different nodes through a connection edge; realizing information transmission among the single items by utilizing classification of the single items, so that each single item contains matching information with other single items, and updating of node vector representationof the single items is further realized; updating the suite node vector representation by utilizing the updated plurality of single-item node vector representations; updating the user node vector representation by using the updated suit node vector representation, and calculating the preference score of the user for each suit by using the updated user node vector representation and the suit node vector representation; and sorting the suites according to the preference scores so as to recommend the suites to the corresponding users. According to the method, the complex interaction information among the user, the suits and the single items can be effectively modeled, and the recommendation performance is improved.

Description

technical field [0001] The invention relates to the fields of recommendation system and graph data mining, in particular to a method for realizing fashion suit recommendation through a graph neural network. Background technique [0002] With the development of e-commerce platforms (Amazon, Taobao, etc.) and fashion social networks (Instagram, Polyvore website, etc.), fashion recommendation has been widely used. But the current recommendation algorithm can only provide users with the recommendation service of fashion items. With the increasing needs of users, the personalized recommendation algorithm for fashion suits has become a hot spot and an urgent problem to be solved. However, there are few researches on this kind of algorithm. [0003] The key to recommending suits to users is to meet two requirements: 1) There must be a good matching effect between the items in the suit; 2) The recommended suits must meet the user's preferences. Most of the current works only focus...

AI Technical Summary

Problems solved by technology

However, this simple modeling method is difficult to learn the complex interaction information between users-suits-items. In addition, these algorithms only perform vector representations for users and items, while ignoring the semantic information of the suit itself

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