How do experienced information lens users use rules?
CHI '89 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
User models: theory, method, and practice
International Journal of Man-Machine Studies
Information filtering and information retrieval: two sides of the same coin?
Communications of the ACM - Special issue on information filtering
Architecting personalized delivery of multimedia information
Communications of the ACM - Special issue on information filtering
Personalized information delivery: an analysis of information filtering methods
Communications of the ACM - Special issue on information filtering
Using collaborative filtering to weave an information tapestry
Communications of the ACM - Special issue on information filtering
Agents that reduce work and information overload
Communications of the ACM
Collaborative interface agents
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
Overview of the second text retrieval conference (TREC-2)
TREC-2 Proceedings of the second conference on Text retrieval conference
Advanced Engineering Mathematics: Maple Computer Guide
Advanced Engineering Mathematics: Maple Computer Guide
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Comparing feature-based and clique-based user models for movie selection
Proceedings of the third ACM conference on Digital libraries
User Models and Filtering Agents for Improved Internet Information Retrieval
User Modeling and User-Adapted Interaction
Tailoring the Interaction with Users in Web Stores
User Modeling and User-Adapted Interaction
Predictive Statistical Models for User Modeling
User Modeling and User-Adapted Interaction
Empirical Evaluation of User Models and User-Adapted Systems
User Modeling and User-Adapted Interaction
Information Filtering: Overview of Issues, Research and Systems
User Modeling and User-Adapted Interaction
Agent Technologies for the Development of Adaptive Web Stores
Agent Mediated Electronic Commerce, The European AgentLink Perspective.
Acquiring User Preferences for Product Customization
UM '01 Proceedings of the 8th International Conference on User Modeling 2001
A Movie Recommendation System—An Application of Voting Theory in User Modeling
User Modeling and User-Adapted Interaction
Annals of Mathematics and Artificial Intelligence
Personalised hypermedia presentation techniques for improving online customer relationships
The Knowledge Engineering Review
The Knowledge Engineering Review
A platform for virtual museums with personalized content
Multimedia Tools and Applications
Personalization of content in virtual exhibitions
SAMT'07 Proceedings of the semantic and digital media technologies 2nd international conference on Semantic Multimedia
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The increasing availability of a large number ofinteractive multi-media information services means thatusers have a large and diverse collection of choices open to them.This diversity and choice may present navigation difficulties to userswhich can dissuade them from using such services.One method of assisting users to navigate through largecollections is to use information filtering to extract only theinformation relevant to an end-user according to his/her long-termpreferences. In this paper, we describe a mechanism to acquire auser‘s long-term preferences (user profile), and thenshow how the acquired profile may be used to recommend selectionsthat may be of interest to the user. The profile is acquired onthe basis of a user‘s habits using a Heuristic-Statisticalapproach, and is used to create selection indices which arethen used during on-line interactions to recommend selections. Our mechanismhas been incorporated into an experimental Video On Demand(VOD) service that is implemented using a client-serverarchitecture. The profile acquisition component isincorporated into a VOD server on a multi-taskingmachine, while the VOD user interface resides on apersonal computer. Our mechanism for acquiring profiles and makingrecommendations has been quantitatively evaluated on thebasis of data collected about movie preferences.