This paper proposes a novel, unified, and systematic approach to combine collaborative and content-based filtering for ranking and user preference prediction. The framework inco...
Adaptive clustering uses external feedback to improve cluster quality; past experience serves to speed up execution time. An adaptive clustering environment is proposed that uses ...
Abraham Bagherjeiran, Christoph F. Eick, Chun-Shen...
This paper outlines first the BET method for task-based evaluation of meeting browsers. ‘Observations of interest’ in meetings are empirically determined by neutral observers ...
Andrei Popescu-Belis, Philippe Baudrion, Mike Flyn...
Successful application of reinforcement learning algorithms often involves considerable hand-crafting of the necessary non-linear features to reduce the complexity of the value fu...
Most learning to rank research has assumed that the utility of different documents is independent, which results in learned ranking functions that return redundant results. The fe...
Aleksandrs Slivkins, Filip Radlinski, Sreenivas Go...