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.
Document type :
Journal articles
Complete list of metadatas

Cited literature [44 references]  Display  Hide  Download

https://hal-lirmm.ccsd.cnrs.fr/lirmm-00798139
Contributor : Pascal Poncelet <>
Submitted on : Friday, March 22, 2019 - 3:59:25 PM
Last modification on : Friday, March 22, 2019 - 4:02:14 PM
Long-term archiving on : Sunday, June 23, 2019 - 4:01:57 PM

File

IJBIDM09.pdf
Files produced by the author(s)

Identifiers

Collections

Citation

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⟩

Share

Metrics

Record views

173

Files downloads

47