In this paper we present a methodology designed to improve the intelligent personalization of news services. Our methodology integrates textual content analysis tasks to achieve an elaborate user model, which represents separately short-term needs and long-term multi-topic interests. The characterization of user’s interests includes his preferences about content, using a wide coverage and non-specific-domain classification of topics, and structure (newspaper sections). The application of implicit feedback allows a proper and dynamic personalization.
CITATION STYLE
De Buenaga Rodríguez, M., Maña López, M. J., Esteban, A. D., & Gómez-Navarro, P. G. (2001). A user model based on content analysis for the intelligent personalization of a news service. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2109, pp. 216–218). Springer Verlag. https://doi.org/10.1007/3-540-44566-8_25
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