Online information services have grown too large for users to navigate without the help of automated tools such as collaborative filtering, which makes recommendations to users ba...
Rapid growth in the amount of data available on social networking sites has made information retrieval increasingly challenging for users. In this paper, we propose a collaborativ...
Social network systems, like last.fm, play a significant role in Web 2.0, containing large amounts of multimedia-enriched data that are enhanced both by explicit user-provided an...
Ioannis Konstas, Vassilios Stathopoulos, Joemon M....
Interdisciplinary collaborations have generated huge impact to society. However, it is often hard for researchers to establish such cross-domain collaborations. What are the patte...
We present PolyLens, a new collaborative filtering recommender system designed to recommend items for groups of users, rather than for individuals. A group recommender is more appr...
Mark O'Connor, Dan Cosley, Joseph A. Konstan, John...