Skip to Main content Skip to Navigation
Conference papers

Statistical machine learning for tracking hypermedia user behaviour

Abstract : We consider the classification and tracking of user navigation patterns for closed world hypermedia. We use a number of statistical machine learning models and compare them on different instances of the classification/tracking problem using a home made access log database. We conclude on the potential and limitations of these methods for user behavior identification and tracking.
Document type :
Conference papers
Complete list of metadatas
Contributor : Lip6 Publications <>
Submitted on : Tuesday, June 6, 2017 - 1:45:08 PM
Last modification on : Tuesday, January 21, 2020 - 3:08:02 PM


  • HAL Id : hal-01533380, version 1


Sylvain Bidel, Laurent Lemoine, Frédéric Piat, Thierry Artières, Patrick Gallinari. Statistical machine learning for tracking hypermedia user behaviour. MLIRUM'03 - 2nd Workshop on Machine Learning, Information Retrieval and User Modeling, Jun 2003, Pittsburgh, PA, United States. ⟨hal-01533380⟩



Record views