Recommender systems are used to predict user preferences for products or services. In order to seek better prediction techniques, data owners of recommender systems such as Netfli...
Chih-Cheng Chang, Brian Thompson, Hui (Wendy) Wang...
The collaborative filtering approach to recommender systems predicts user preferences for products or services by learning past useritem relationships. In this work, we propose no...
Collaborative filtering has proven to be valuable for recommending items in many different domains. In this paper, we explore the use of collaborative filtering to recommend resea...
Sean M. McNee, Istvan Albert, Dan Cosley, Prateep ...
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...
Conversational recommender systems (CRSs) assist online users in their information-seeking and decision making tasks by supporting an interactive process. Although these processes...