Data sparsity, scalability and prediction quality have been recognized as the three most crucial challenges that every collaborative filtering algorithm or recommender system conf...
Traditionally, collaborative filtering (CF) algorithms used for recommendation operate on complete knowledge. This makes these algorithms hard to employ in a decentralized contex...
Different buyers exhibit different purchasing behaviors. Some rush to purchase new products while others tend to be more cautious, waiting for reviews from people they trust. In...
A particularly challenging task for recommender systems (RSs) is deciding whether to recommend an item that received a variety of high and low scores from its users. RSs that inco...
Patricia Victor, Chris Cornelis, Martine De Cock, ...
Collaborative filtering requires a centralized rating database. However, within a peer-to-peer network such a centralized database is not readily available. In this paper, we pro...
Jun Wang, Johan A. Pouwelse, Reginald L. Lagendijk...