Learning and Revising User Profiles: The Identification ofInteresting Web Sites
Machine Learning - Special issue on multistrategy learning
Cumulated gain-based evaluation of IR techniques
ACM Transactions on Information Systems (TOIS)
A Taxonomy of Recommender Agents on theInternet
Artificial Intelligence Review
Optimizing search engines using clickthrough data
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
An efficient boosting algorithm for combining preferences
The Journal of Machine Learning Research
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
Ontology-Based Personalised and Context-Aware Recommendations of News Items
WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
Comparison of implicit and explicit feedback from an online music recommendation service
Proceedings of the 1st International Workshop on Information Heterogeneity and Fusion in Recommender Systems
Recommending biomedical resources: A fuzzy linguistic approach based on semantic web
International Journal of Intelligent Systems - New Trends for Ontology-Based Knowledge Discovery
Taking Advantage of Semantics in Recommendation Systems
Proceedings of the 2010 conference on Artificial Intelligence Research and Development: Proceedings of the 13th International Conference of the Catalan Association for Artificial Intelligence
Making the most of TV on the move: My newschannel
Information Sciences: an International Journal
A recommendation strategy based on user behavior in digital ecosystems
Proceedings of the International Conference on Management of Emergent Digital EcoSystems
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
Turist@: Agent-based personalised recommendation of tourist activities
Expert Systems with Applications: An International Journal
A preference learning approach to sentence ordering for multi-document summarization
Information Sciences: an International Journal
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
Dynamic adaptation of numerical attributes in a user profile
Applied Intelligence
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One of the most challenging tasks in the development of recommender systems is the design of techniques that can infer the preferences of users through the observation of their actions. Those preferences are essential to obtain a satisfactory accuracy in the recommendations. Preference learning is especially difficult when attributes of different kinds (numeric or linguistic) intervene in the problem, and even more when they take multiple possible values. This paper presents an approach to learn user preferences over numeric and multi-valued linguistic attributes through the analysis of the user selections. The learning algorithm has been tested with real data on restaurants, showing a very good performance.