Personalized intelligent clothing matching recommendation method combined with knowledge graph

Abstract

The present invention relates to the technical field of recommendation systems, in particular to a personalized intelligent clothing collocation recommendation method combined with knowledge graphs, which acquires clothing product information on an e-commerce platform and user clothing interaction information and constructs a knowledge graph; models the knowledge graph, and Each entity and relationship in the knowledge map is learned to obtain entity vectors and relationship vectors; the entity vector and relationship vector are combined with a hybrid recommendation system to predict the rating of single-item clothing and obtain clothing single-item recommendation results; calculate pairwise The matching index of clothing items, automatically match two clothing items with high matching index and predict the score, and make the final TOP-N suit recommendation result according to the score. This method makes online clothing suit recommendation more intelligent.

Description

technical field [0001] The invention relates to the technical field of recommendation systems, in particular to a personalized intelligent clothing collocation recommendation method combined with knowledge graphs. Background technique [0002] With the rapid development of mobile Internet and the wide application of e-commerce, various e-commerce platforms have emerged one after another, such as Taobao, Jingdong, Tmall, Vipshop, etc. However, with the development of the information age, most websites are facing the problems of information overload and information lost, so to address these two problems, the recommendation system came into being. [0003] Among them, the recommendation system also plays an important role on various Internet platforms. Through the recommendation system, users can more efficiently and quickly find products or information that they are interested in or have potential interests in. Based on the user's historical behavior information, the recommen...

AI Technical Summary

Problems solved by technology

However, there are still a series of problems in the traditional recommendation system, such as low recommendation accuracy, unexplainable recommendation, data sparsity and cold start problems, etc.

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