Two major challenges in collaborative filtering are the efficiency of the algorithms and the quality of the recommendations. A variety of machine learning methods have been applie...
Memory-based methods for collaborative filtering predict new ratings by averaging (weighted) ratings between, respectively, pairs of similar users or items. In practice, a large ...
Jun Wang, Arjen P. de Vries, Marcel J. T. Reinders
If recommenders are to help people be more productive, they need to support a wide variety of real-world information seeking tasks, such as those found when seeking research paper...
Sean M. McNee, Nishikant Kapoor, Joseph A. Konstan
This paper presents a Case-Based Reasoning approach for the personalized access and the students’ coauthoring tasks in on-line repositories of Learning Objects (LOs). The person...
: Web usage mining, possibly used in conjunction with standard approaches to personalization such as collaborative filtering, can help address some of the shortcomings of these tec...
Bamshad Mobasher, Honghua Dai, Tao Luo, Miki Nakag...