Collaborative filtering is a very useful general technique for exploiting the preference patterns of a group of users to predict the utility of items to a particular user. Previou...
The majority of recommender systems are designed to make recommendations for individual users. However, in some circumstances the items to be selected are not intended for persona...
Linas Baltrunas, Tadas Makcinskas, Francesco Ricci
Abstract. This paper describes a new way of implementing an intelligent web caching service, based on an analysis of usage. Since the cache size in software is limited, and the sea...
Data sparsity is a major problem for collaborative filtering (CF) techniques in recommender systems, especially for new users and items. We observe that, while our target data are...
Weike Pan, Evan Wei Xiang, Nathan Nan Liu, Qiang Y...
We describe a recommender system which uses a unique combination of content-based and collaborative methods to suggest items of interest to users, and also to learn and exploit it...