Personalized costume matching recommendation method and system using time factor

Abstract

The invention discloses a personalized costume matching recommendation method and system using a time factor. The method comprises the steps of collecting a data set, constructing a heterogeneous graph, learning feature representations of clothes and a user and general rules of clothes matching, learning preference rules of the user for a suit, calculating personalized matching scores, training a heterogeneous graph network, and obtaining a scoring model integrating a clothes matching degree and user personal preferences, and finally, the user obtaining personalized costume matching recommendation according to the model. According to the method, the heterogeneous graph neural network is constructed, different preference degrees of different interactive behaviors of a user on clothes are considered, and the influence rule of time factors on user preferences is learned by integrating user interactive behavior time and clothes node time; and finally, the preference of the user to the suit is learned according to the historical record and the clothing information of the user and the preference of the user to the single item, the feature representation and the internal relation of the clothing and the user are modeled, and the personalized clothing matching recommendation method is realized.

Description

technical field [0001] The present invention relates to the field of machine learning and clothing recommendation, in particular to a method, system, device and storage medium for personalized clothing collocation recommendation using time factors. Background technique [0002] The rapid development of e-commerce has brought more clothing choices for people. Compared with the era of material scarcity, people's concerns about clothing not only include the product quality of clothing, but also put forward higher requirements for the beauty of clothing matching, but not everyone is good at clothing matching. In order to provide users with outfit suggestions and meet users' needs for clothing matching, the recommendation system for clothing matching has attracted the attention of academia and industry. [0003] The current clothing collocation recommendation methods are mainly divided into two categories: the general clothing collocation recommendation method that focuses on th...

AI Technical Summary

Problems solved by technology

The main problems solved by the present invention are as follows: one is that the existing personalized clothing collocation recommendation method ignores the influence of time factors on the recommendation results, and ignores the dynamic interest of users and the popularity change of clothing; the other is in the modeling of user preferences , giving equal consideration to different behaviors of users; third, the current method cannot handle the collocation scoring of other types of clothing, and does not consider the popularity of single items in suit combinations

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