J Deng, X Ran, Y Wang, LY Zhang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Most previous studies on matrix factorization (MF)-based collaborative filtering (CF) have focused solely on user rating information for predicting recommendations. However, to …
Recommender systems are promising for providing personalized favorite services. Collaborative filtering (CF) technologies, making prediction of users' preference based on …
Collaborative Filtering (CF) is a popular way to build recommender systems and has been successfully employed in many applications. Generally, two kinds of approaches to CF, the …
D kumar Bokde, S Girase… - CoRR, abs …, 2015 - researchgate.net
ABSTRACT Recommendation Systems apply Information Retrieval techniques to select the online information relevant to a given user. Collaborative Filtering (CF) is currently most …
In designing modern recommender systems, item feature information (or side information) is often ignored as most models focus on exploiting rating information. However, the side …
Recommender systems, which can significantly help users find their interested items from the information era, has attracted an increasing attention from both the scientific and …
K Anwar, A Zafar, A Iqbal - International Journal of Information Technology, 2024 - Springer
Recommender Systems are useful information filtering tools that have reduced information overload over the web. Collaborative filtering (CF) is one of the extensively used …
Collaborative Filtering (CF) is the most widely used prediction technique in recommender systems. It makes recommendations based on ratings that users have assigned to items …
W Pan, Z Ming - IEEE Intelligent Systems, 2017 - ieeexplore.ieee.org
Factorization-and neighborhood-based methods have been recognized as state-of-the-art approaches for collaborative recommendation tasks. In this article, the authors take user …