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View all- Pu YFan RChen JZhu ZLian DChen E(2024)Automated Sparse and Low-Rank Shallow Autoencoders for RecommendationACM Transactions on Recommender Systems10.1145/3656482Online publication date: 10-Apr-2024
Collaborative filtering (CF) works have demonstrated the robust capabilities of Shallow Autoencoders on implicit feedback, showcasing highly competitive performance with other reasonable approaches (e.g., iALS and VAE-CF). However, despite their dual ...
Collaborative filtering systems represent services of personalized that aim at predicting a user’s interest on some items available in the application systems. With the development of electronic commerce, the number of users and items grows rapidly, ...
Collaborative Filtering (CF) has been widely used in many recommender systems over the past decades. Conventional CF-based methods mainly consider the ratings given to items via users and suffer from the sparsity and cold-start problems very much. ...
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