HIGHLIGHTS
SUMMARY
Currently, along with the development and variety of products and services, recommender systems are increasingly widely used in areas such as online shopping (e_g, Amazon), e-news (e_g, Yahoo! The traditional recommender system (also known as a two-dimensional recommender system) only uses two information dimensions about users and items, including user preferences for items (often reflected in ratings), user profiles and item content features to make recommendations. CARSs are an extension of traditional recommender systems that give recommendations to users and consider contextual information (e_g, weather, time, and the user`s mood) or . . .
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