Abstract—Collaborative or “Social” filtering has been successfully deployed over the years as a technique for analysing large amounts of user-preference knowledge to predict...
John O'Donovan, Brynjar Gretarsson, Svetlin Bostan...
Current knowledge bases suffer from either low coverage or low accuracy. The underlying hypothesis of this work is that user feedback can greatly improve the quality of automatica...
Gjergji Kasneci, Jurgen Van Gael, Ralf Herbrich, T...
Recommender systems help people to find information that is interesting to them. However, current recommendation techniques only address the user's short-term and long-term i...
Mark van Setten, Mettina Veenstra, Anton Nijholt, ...
Collaborative filtering systems make recommendations based on the accumulation of ratings by many users. The process has a case-based reasoning flavor: recommendations are generate...
We present and evaluate various content-based recommendation models that make use of user and item profiles defined in terms of weighted lists of social tags. The studied approach...