Analysis of Dwell Times in Web Usage Mining

Patrick Mair, Marcus Hudec

Publication: Chapter in book/Conference proceedingChapter in edited volume


In this contribution we focus on dwell times a user spends on various areas of a web site within a session. We assume that dwell times may be adequately modeled by a Weibull distribution which is a flexible and common approach in survival analysis. Furthermore we introduce heterogeneity by various parameterizations of dwell time densities by means of proportional hazards models. According to these assumptions the observed data stem from a mixture of Weibull densities. Estimation is based on EM-algorithm and model selection may be guided by BIC. Identification of mixture components corresponds to a segmentation of users/sessions. A real life data set stemming from the analysis of a world wide operating eCommerce application is provided. The corresponding computations are performed with the mixPHM package in R.
Original languageEnglish
Title of host publicationData Analysis, Machine Learning and Applications
Editors C. Preisach, H. Burghardt, L. Schmidt-Thieme & R. Decker
Place of PublicationBerlin
Pages593 - 600
Publication statusPublished - 1 Mar 2008

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