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...
Abstract--Recommender systems are gaining widespread acceptance in e-commerce applications to confront the "information overload" problem. Providing justification to a re...
The open nature of collaborative recommender systems allows attackers who inject biased profile data to have a significant impact on the recommendations produced. Standard memory-...
Abstract. Many e-commerce sites use a recommendation system to filter the specific information that a user wants out of an overload of information. Currently, the usefulness of the...
In order to assist a power plant operator to face unusual situations, we have developed an intelligent assistant that explains the suggested commands generated by an MDP-based pla...
Francisco Elizalde, Luis Enrique Sucar, Alberto Re...