Esther Kang

Learning Popularity-Aware User Representations for Sequential Recommendation via Retrieval-Augmentation

Sequential recommendation methods are important in recommender systems, as they capture users’ dynamic interests from their historical behavior sequences. However, most existing methods have two limitations. First, they heavily rely on semantics from only a target user's interact...