Statistical machine learning for tracking hypermedia user behaviour
Résumé
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.