—The number of resources or items that users can now access when navigating on the Web or using e-services, is so huge that these might feel lost due to the presence of too much ...
The potential benefit of integrating contextual information for recommendation has received much research attention recently, especially with the ever-increasing interest in mobil...
Yize Li, Jiazhong Nie, Yi Zhang, Bingqing Wang, Ba...
Abstract. In this paper we propose an incremental item-based collaborative filtering algorithm. It works with binary ratings (sometimes also called implicit ratings), as it is typi...
Since the beginning of the 1990's, the Internet has constantly grown, proposing more and more services and sources of information. The challenge is no longer to provide users ...
While a user’s preference is directly reflected in the interactive choice process between her and the recommender, this wealth of information was not fully exploited for learni...
Shuang-Hong Yang, Bo Long, Alexander J. Smola, Hon...