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 improvementsI documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
