Recommender systems suggest potentially relevant content by evaluating user preferences and are essential in reducing information overload. However, when users join a new online platform, recommendation systems often struggle to understand their preferences. With no prior interactions in the new environment, these “cold-start” users are difficult to serve accurately.
New deep learning framework solves the cold-start problem
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