Communications of the ACM
Learning and Revising User Profiles: The Identification ofInteresting Web Sites
Machine Learning - Special issue on multistrategy learning
A Taxonomy of Recommender Agents on theInternet
Artificial Intelligence Review
Implicit feedback for inferring user preference: a bibliography
ACM SIGIR Forum
Implicit interaction profiling for recommending spatial content
Proceedings of the 13th annual ACM international workshop on Geographic information systems
New Recommendation Techniques for Multicriteria Rating Systems
IEEE Intelligent Systems
Flickr tag recommendation based on collective knowledge
Proceedings of the 17th international conference on World Wide Web
IEEE Transactions on Knowledge and Data Engineering
Recommending biomedical resources: A fuzzy linguistic approach based on semantic web
International Journal of Intelligent Systems - New Trends for Ontology-Based Knowledge Discovery
Making the most of TV on the move: My newschannel
Information Sciences: an International Journal
Buzzer: online real-time topical news article and source recommender
AICS'09 Proceedings of the 20th Irish conference on Artificial intelligence and cognitive science
Personalized recommendation of popular blog articles for mobile applications
Information Sciences: an International Journal
On using the real-time web for news recommendation & discovery
Proceedings of the 20th international conference companion on World wide web
Terms of a feather: content-based news recommendation and discovery using twitter
ECIR'11 Proceedings of the 33rd European conference on Advances in information retrieval
Mining the real-time web: A novel approach to product recommendation
Knowledge-Based Systems
Turist@: Agent-based personalised recommendation of tourist activities
Expert Systems with Applications: An International Journal
User satisfaction in long term group recommendations
ICCBR'11 Proceedings of the 19th international conference on Case-Based Reasoning Research and Development
Ontology-based user profile learning
Applied Intelligence
On-line dynamic adaptation of fuzzy preferences
Information Sciences: an International Journal
SigTur/E-Destination: Ontology-based personalized recommendation of Tourism and Leisure Activities
Engineering Applications of Artificial Intelligence
A semantic social network-based expert recommender system
Applied Intelligence
Automatic preference learning on numeric and multi-valued categorical attributes
Knowledge-Based Systems
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Recommender systems try to help users in their decisions by analyzing and ranking the available alternatives according to their preferences and interests, modeled in user profiles. The discovery and dynamic update of the users' preferences are key issues in the development of these systems. In this work we propose to use the information provided by a user during his/her interaction with a recommender system to infer his/her preferences over the criteria used to define the decision alternatives. More specifically, this paper pays special attention on how to learn the user's preferred value in the case of numerical attributes. A methodology to adapt the user profile in a dynamic and automatic way is presented. The adaptations in the profile are performed after each interaction of the user with the system and/or after the system has gathered enough information from several user selections. We have developed a framework for the automatic evaluation of the performance of the adaptation algorithm that permits to analyze the influence of different parameters. The obtained results show that the adaptation algorithm is able to learn a very accurate model of the user preferences after a certain amount of interactions with him/her, even if the preferences change dynamically over time.