Abstract
This paper presents a system for personalization of web contents based on a user model that stores long term and short term interests. Long term interests are modeled through the selection of specific and general categories, and keywords for which the user needs information. However, user needs change over time as a result of his interaction with received information. For this reason, the user model must be capable of adapting to those shifts in interest. In our case, this adaptation of the user model is performed by a short term model obtained from user provided feedback. The evaluation performed with 100 users during 15 days has determined that the combined use of long and short term models performs best when specific and general categories and keywords are used together for the long term model. © Springer-Verlag 2004.
Cite
CITATION STYLE
Díaz, A., & Gervás, P. (2004). Adaptive user modeling for personalization of web contents. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3137, 65–74. https://doi.org/10.1007/978-3-540-27780-4_10
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