In this paper we carry out a site-centric clickstream analysis by fitting a probabilistic model to the click sequences of surfers browsing an e-commerce Web site. In particular, surfers’ paths are modeled as observations originating from a finite mixture of Markov chains which takes values in the site’s page-space. We preliminarily tackle the problem of making inference on the number of distinct visits in which each surfers’ sequence of clicks can be divided. We then deal with goodness-of-fit testing of the model to real data, exploring the heterogeneity of surfers. Finally, by using a simple model with only two components, we shed light on the relationship between surfing behavior and tendency to on-line purchasing.

A Markovian mixture model for Web data / L., DI SCALA; LA ROCCA, Luca. - In: STATISTICA APPLICATA. - ISSN 1125-1964. - STAMPA. - 14:(2002), pp. 143-154.

A Markovian mixture model for Web data

LA ROCCA, Luca
2002

Abstract

In this paper we carry out a site-centric clickstream analysis by fitting a probabilistic model to the click sequences of surfers browsing an e-commerce Web site. In particular, surfers’ paths are modeled as observations originating from a finite mixture of Markov chains which takes values in the site’s page-space. We preliminarily tackle the problem of making inference on the number of distinct visits in which each surfers’ sequence of clicks can be divided. We then deal with goodness-of-fit testing of the model to real data, exploring the heterogeneity of surfers. Finally, by using a simple model with only two components, we shed light on the relationship between surfing behavior and tendency to on-line purchasing.
14
143
154
A Markovian mixture model for Web data / L., DI SCALA; LA ROCCA, Luca. - In: STATISTICA APPLICATA. - ISSN 1125-1964. - STAMPA. - 14:(2002), pp. 143-154.
L., DI SCALA; LA ROCCA, Luca
File in questo prodotto:
Non ci sono file associati a questo prodotto.
Pubblicazioni consigliate

Caricamento pubblicazioni consigliate

Licenza Creative Commons
I metadati presenti in IRIS UNIMORE sono rilasciati con licenza Creative Commons CC0 1.0 Universal, mentre i file delle pubblicazioni sono rilasciati con licenza Attribuzione 4.0 Internazionale (CC BY 4.0), salvo diversa indicazione.
In caso di violazione di copyright, contattare Supporto Iris

Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11380/454249
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact