Recommender Systems, based on collaborative filtering (CF), aim to accurately predict user tastes, by minimising the mean error achieved on hidden test sets of user ratings, afte...
If recommenders are to help people be more productive, they need to support a wide variety of real-world information seeking tasks, such as those found when seeking research paper...
Sean M. McNee, Nishikant Kapoor, Joseph A. Konstan
We describe the WebCLEF 2008 task. Similarly to the 2007 edition of WebCLEF, the 2008 edition implements a multilingual "information synthesis" task, where, for a given t...
Traditional adaptive filtering systems learn the user’s interests in a rather simple way – words from relevant documents are favored in the query model, while words from irre...
We study the problem of designing a mechanism to rank items in forums by making use of the user reviews such as thumb and star ratings. We compare mechanisms where forum users rat...
Anish Das Sarma, Atish Das Sarma, Sreenivas Gollap...