Burgeoning information volume on the internet has created increasing interest in automated
filtering, refinement and presentation of relevant information to users. Recommender …

We are developing a web-based movie recommender system that catches and reasons with
user preferences to pro-actively recommend movies. It combines voting based ranking …

Personal assistant agents embody a clearly beneficial application of intelligent agent
technology. A particular kind of assistant agents, recommender systems (RSs), can be used …

This paper introduces a new approach for decision support on the internet. It is
characterized by a preference-based filtering relying on the integration of contentbased and …

This paper describes DIVA, a decision-theoretic agent for recommending movies that
contains a number of novel features. DIVA represents user preferences using pairwise …

Our research agenda focuses on building software agents that can employ user modeling
techniques to facilitate information access and management tasks. Personal assistant …

Movie recommender systems attempt to find movies which are of interest for their users.
However, as new movies are added, and new users join movie recommendation services …

Collaborative filtering methods have been applied to a number of domains like books,
videos, audio CDs and Usenet news. These systems require some effort on the part of users …

Personalised recommender systems learn about a user's needs, and identify and suggest
information items (news articles, images, videos, etc.) that meet those needs. User needs …

Personalized recommender systems improve access to relevant items and information by
making personalized suggestions based on previous items of an individual user's likes and …