JSM 2004 - Toronto

Abstract #301100

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Activity Number: 46
Type: Topic Contributed
Date/Time: Sunday, August 8, 2004 : 4:00 PM to 5:50 PM
Sponsor: Section on Statistical Computing
Abstract - #301100
Title: A Bayesian Model for Relating Browsing Behavior to Site Structure on the World Wide Web
Author(s): Murali Haran*+
Companies: National Institute of Statistical Sciences
Address: 19 T W. Alexander Dr., Research Triangle Park, NC, 27709,
Keywords: hierarchical Bayes ; World Wide Web ; clickstream data
Abstract:

A critical problem for users of the World Wide Web is that many sites are difficult to navigate, hard to use, and have confusing structure. This can be largely attributed to a mismatch between the designer's understanding of the structure for the web site, and actual user behavior. One approach to understanding user behavior is to exploit the rich instrumentation in the online world. Web servers create voluminous log files that record every hit to every page on the site. We propose Bayesian statistical models that use this data to relate visitor transition patterns to site structure. These models help relate site activity to site structure, can correlate site modifications with activity changes, and make stochastic predictions. We illustrate our approach with an example from a commerce web site.

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