Recommender systems improve access to relevant products and information by making personalized suggestions based on previous examples of a user's likes and dislikes. Most exi...
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
Collaborative Filtering based on similarity suffers from a variety of problems such as sparsity and scalability. In this paper, we propose an ontological model of trust between us...
Alireza Zarghami, Soude Fazeli, Nima Dokoohaki, Mi...
Personalization systems based upon users' surfing behavior analysis imply three phases: data collection, pattern discovery and recommendation. Due to the dimension of log file...
Capturing the context of a user's query from the previous queries and clicks in the same session may help understand the user's information need. A context-aware approac...