Analysis of Dwell Times in Web Usage Mining

Patrick Mair, Marcus Hudec

Publikation: Beitrag in Buch/KonferenzbandBeitrag in Sammelwerk

Abstract

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.
OriginalspracheEnglisch
TitelData Analysis, Machine Learning and Applications
Redakteure/-innen C. Preisach, H. Burghardt, L. Schmidt-Thieme & R. Decker
ErscheinungsortBerlin
VerlagSpringer
Seiten593 - 600
PublikationsstatusVeröffentlicht - 1 März 2008

Dieses zitieren