We presetn a new version of SiteIF, a recommender system for a Web site of multilingual news. Exploiting a content-based document representation, we describe a model of the user's interests based on word senses rather than on simply words. There are two main advantages of a content-based approach: first, the model predictions, being based on senses rather then words, are more accurate; second, the model is language independent, allowing navigation in multilingual sites. We also preport the results of a comparative experiment (word-based vs. sense-based) that has been carried out to give a quantitative estimation of the content-based approach improvements

User Modelling for News Web Sites with Content-Based Techniques

Magnini, Bernardo;Strapparava, Carlo
2002-01-01

Abstract

We presetn a new version of SiteIF, a recommender system for a Web site of multilingual news. Exploiting a content-based document representation, we describe a model of the user's interests based on word senses rather than on simply words. There are two main advantages of a content-based approach: first, the model predictions, being based on senses rather then words, are more accurate; second, the model is language independent, allowing navigation in multilingual sites. We also preport the results of a comparative experiment (word-based vs. sense-based) that has been carried out to give a quantitative estimation of the content-based approach improvements
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11582/789
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