WebUser: mining unexpected web usage. (27th January 2011)

• Record Type: Journal Article
• Authors: Li, Dong; Laurent, Anne; Poncelet, Pascal
• Is Part Of: International journal of business intelligence and data mining. Volume 6:Number 1(2011)
• Page Start: 90
• Page End: 111
• Publication Date: 2011-01-27
• Subjects: data mining -- web usage mining -- log analysis -- unexpected usage -- sequence rules -- concept hierarchies -- web access logs -- belief systems -- temporal relations -- semantics -- prior knowledge -- web content personalisation -- recommendations -- site structure optimisation -- critical event prediction; 006.312
• Languages: English
• ISSNs: 1743-8187

Abstract

Web usage mining has been much concentrated on the discovery of relevant user behaviours from web access record data. In this paper, we present WebUser, an approach to discover unexpected usage in web access log. We present a belief-driven method for extracting unexpected web usage sequences, where the belief system consists of a temporal relation and semantics constrained sequence rules acquired with respect to prior knowledge. Our experiments show the effectiveness and usefulness of the proposed approach. Furthermore, discovered rules of unexpected web usage can be used for web content personalisation and recommendation, site structure optimisation and critical event prediction.