A ranking approach, ListRank-MF, is proposed for collaborative filtering that combines a list-wise learning-to-rank algorithm with matrix factorization (MF). A ranked list of item...
The interest among a geographically distributed user base to mine massive collections of scientific data propels the need for efficient data dissemination solutions. An optimal dat...
: Automated collaborative filtering is a popular technique for reducing information overload. In this paper, we propose a new approach for the collaborative filtering using local...
This paper aims to demonstrate that the principles of adaptation and user modeling, especially social annotation, can be integrated fruitfully with those of the Web 2.0 paradigm a...
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...