Information Sciences: an International Journal
Expert Systems with Applications: An International Journal
Information Sciences: an International Journal
International Journal of Intelligent Systems
A balanced memory-based collaborative filtering similarity measure
International Journal of Intelligent Systems
On-line dynamic adaptation of fuzzy preferences
Information Sciences: an International Journal
Recommending social network applications via social filtering mechanisms
Information Sciences: an International Journal
Dynamic adaptation of numerical attributes in a user profile
Applied Intelligence
Automatic preference learning on numeric and multi-valued categorical attributes
Knowledge-Based Systems
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One of the key issues in dynamic research areas, such as that of biomedical sciences, is the development of tools capable to retrieve and provide users relevant resources from large repositories according to their information needs. In this paper, we present a filtering and recommender system that applies Semantic Web technologies and fuzzy linguistic modeling techniques to provide users valuable information about resources that fit their interests. To carry out the recommendation process, we have defined three software agents (interface, task, and information agents) that are distributed in a five level hierarchical architecture. The system is also capable of to deal with incomplete information to define enriched user profiles and, therefore, soften the problem of cold start. A simple evaluation has been carried out, and the experimental outcomes reveal a reasonable good performance of the system in terms of precision and recall. © 2010 Wiley Periodicals, Inc.