Collaborative filtering generates recommendations by exploiting user-item similarities based on rating data, which often contains numerous unrated items. To predict scores for unrated items, matrix ...

Abstract: Deep neural networks have found wide applications in fields such as natural language processing, language translation, computer vision, and speech recognition, including recommendation ...

Abstract: Recommender systems have undergone more than three decades of continuous development, from early collaborative filtering techniques and matrix factorization to the integration of deep ...