Authors:
Anne Boyer
and
Sylvain Castagnos
Affiliation:
LORIA, Université Nancy 2, France
Keyword(s):
Distributed Collaborative Filtering, Recommender Systems, Personalization, Grid Computing, Scalability, Privacy.
Related
Ontology
Subjects/Areas/Topics:
Agents
;
Artificial Intelligence
;
Communities of Interest
;
Data Engineering
;
e-Business
;
Enterprise Information Systems
;
Grid Computing
;
Internet Technology
;
Ontologies and the Semantic Web
;
Personalized Web Sites and Services
;
Society, e-Business and e-Government
;
Technology Platforms
;
User Modeling
;
Web Information Systems and Technologies
;
Web Interfaces and Applications
;
Web Personalization
Abstract:
The size of available data on Internet is growing faster than human ability to treat it. Therefore, it becomes more and more difficult to identify the most relevant information, even for skilled people using efficient search engines. A way to cope with this problem is to automatically recommend data in accordance with users’ preferences. Among others, collaborative filtering processes help users to find interesting items by comparing them with users having the same tastes. This paper describes a new user-centered recommender system relying on collaborative filtering and grid computing. Our model has been implemented in a Peer-to-Peer architecture. It has been especially designed to deal with problems of scalability and privacy. Moreover, it adapts its prediction computations to the density of the user neighborhood.