Exploitation du skipping pour la modélisation prédictive des usages du web: Vers une meilleure prise en compte du bruit
Identifieur interne : 001F04 ( Main/Merge ); précédent : 001F03; suivant : 001F05Exploitation du skipping pour la modélisation prédictive des usages du web: Vers une meilleure prise en compte du bruit
Auteurs : Geoffray Bonnin [France] ; Armelle Brun [France] ; Anne Boyer [France]Source :
- Revue d'intelligence artificielle [ 0992-499X ] ; 2012.
Descripteurs français
- Pascal (Inist)
- Wicri :
- topic : Recommandation.
English descriptors
- KwdEn :
Abstract
Predictive web usage modeling has undergone an intense period of investigation until the late 90's. However, two features of web browsing have rarely been taken into account: the presence of noise and parallel browsing. In this paper, we propose a new model, the SBR model (Skipping-Based Recommender) which uses a technique called skipping, and is able to take into account these features. In a series of experimental studies, we put forward the various contributions that this model possesses and show that its quality surpasses that of the state-of-the-art.
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Pascal:13-0093408Le document en format XML
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<front><div type="abstract" xml:lang="en">Predictive web usage modeling has undergone an intense period of investigation until the late 90's. However, two features of web browsing have rarely been taken into account: the presence of noise and parallel browsing. In this paper, we propose a new model, the SBR model (Skipping-Based Recommender) which uses a technique called skipping, and is able to take into account these features. In a series of experimental studies, we put forward the various contributions that this model possesses and show that its quality surpasses that of the state-of-the-art.</div>
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