A multi-angle hybrid recommendation method for cosmetics

Abstract

A multi-angle mixed recommendation method for cosmetics, comprising the following steps: 1) collecting user data, including the user's ip address and deriving the user's geographic location, current season, and user rating information for cosmetics; 2) according to the user's 3) Perform singular value decomposition preprocessing on the matrix that needs to be calculated for similarity; 4) Obtain the set S of cosmetics that have not been rated by the user from the user-score matrix; 5) Combine user skin attributes , the cosmetic popularity, the mapping relationship between the cosmetic label and the corresponding label of the skin attribute, and the estimated value of the cosmetic is given; 6) The cosmetics in the unrated cosmetic set S are sorted from high to low according to the estimated value as the recommendation result, and the recommendation results are presented in order to the user. The invention realizes personalized recommendation and improves the user experience of the user in cosmetic selection.

Description

technical field [0001] The invention relates to the field of information technology, in particular to a multi-angle mixed recommendation method for cosmetics. Background technique [0002] With the development of Internet technology, people are in an era of information explosion. In the face of massive information data at this stage, certain rules are needed to screen and filter massive data for users and present the information that users are most interested in in front of users, saving It shortens the time for users to screen information and increases the user experience at the same time. [0003] The emergence of search engines has solved the problem of information screening to a certain extent, but it cannot actively provide information for users. At the same time, the information can be actively displayed among the people who are interested in it. In the cosmetics industry, the types and effects of cosmetics are complex, and users may not know much about the products ...

AI Technical Summary

Problems solved by technology

[0004] In order to overcome the shortcomings that the current recommendation system cannot make personalized recommendations for factors such as cosmetic characteristics, user skin attributes, cosmetic popularity, and user environmental characteristics, the present invention provides a multi-angle mixed recommendation method for cosmetics, specifically Said that it is a multi-dimensional information modeling of cosmetics users, mixing multiple recommendation algorithms, using the user's ratings on cosmetics, cosmetic labels, user skin attributes, and the mapping relationship between skin attributes and cosmetic labels to achieve combined user Preferences, user skin characteristics and current popular products are a system for the purpose of personalized recommendation of cosmetics for users, so as to improve user experience in cosmetics selection

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