WebUser: mining unexpected web usage

Haoyuan Li 1 Anne Laurent 1 Pascal Poncelet 1
1 TATOO - Fouille de données environnementales
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
Abstract : Web usage mining has been much concentrated on the discovery of relevant user behaviours from Web access record data. In this paper, we present WebUser, an approach to discover unexpected usage in Web access log. We present a belief-driven method for extracting unexpected Web usage sequences, where the belief system consists of a temporal relation and semantics constrained sequence rules acquired with respect to prior knowledge. Our experiments show the effectiveness and usefulness of the proposed approach. Further, discovered rules of unexpected Web usage can be used for Web content personalisation and recommendation, site structure optimisation, and critical event prediction.
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Article dans une revue
International Journal of Business Intelligence and Data Mining, Inderscience, 2011, 6 (1), pp.90-111. 〈10.1504/IJBIDM.2011.038276〉
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https://hal-lirmm.ccsd.cnrs.fr/lirmm-00798139
Contributeur : Pascal Poncelet <>
Soumis le : vendredi 8 mars 2013 - 09:49:39
Dernière modification le : jeudi 11 janvier 2018 - 06:26:17

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Haoyuan Li, Anne Laurent, Pascal Poncelet. WebUser: mining unexpected web usage. International Journal of Business Intelligence and Data Mining, Inderscience, 2011, 6 (1), pp.90-111. 〈10.1504/IJBIDM.2011.038276〉. 〈lirmm-00798139〉

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