With the rapid growth of the Web, users get easily lost in the rich hyper structure on the web. Providing relevant information to the users to supply to their needs is the primary goal of the owners of these websites. Web mining is one of the techniques that could help the websites owner in this direction. Web mining was categorized into three categories such as web content mining, web usage mi...

Surfing the Web has become an important daily activity for many users. Discovering and understanding web users’ surfing behavior are essential for the development of successful web monitoring and recommendation systems. To capture users’ web access behavior, one promising approach is web usage mining which discovers interesting and frequent user access patterns from web usage logs. Web usage mi...

Recently, the applications of Web usage mining are more and more concentrated on finding valuable user behaviors from Web navigation record data, where the sequential pattern model has been well adapted. However with the growth of the explored user behaviors, the decision makers will be more and more interested in unexpected behaviors, but not only in those already confirmed. In this paper, we ...

The obtention of a set of homogeneous classes of pages according to the browsing patterns identified in web server log files can be very useful for the analysis of organization of the site and of its adequacy to user needs. Such a set of homogeneous classes is often obtained from a dissimilarity measure between the visited pages defined via the visits extracted from the logs. There are however ...

Recently Web mining has become a hot research topic, which combines two of the prominent research areas comprising of data mining and the World Wide Web (WWW) [8]. Web usage mining attempts to discover useful knowledge from the secondary data obtained from the interactions of the users with the Web. Web usage mining has become very critical for effective Web site management, business and suppor...

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 acquir...

Analyzing access log les is usually called Web Usage Mining and provides very useful knowledge for performance enhancement, restructuring a Web site and customer targeting in electronic commerce. These techniques are however limited to a single Web server log le analysis (Intrasite Web Usage Mining). We propose in this paper the Web Usage Mining Inter-Sites notion in order to study the behaviou...

Recently Web mining has become a hot research topic, which combines two of the prominent research areas comprising of data mining and the World Wide Web (WWW). Web usage mining attempts to discover useful knowledge from the secondary data obtained from the interactions of the users with the Web. Web usage mining has become very critical for effective Web site management, business and support se...

Web usage mining differs from collaborative filtering in the fact that we are not interested in explicitly discovering user profiles but rather usage profiles. When preprocessing a log file we do not concentrate on efficient identification of unique users but rather try to identify separate user sessions. These sessions are then used to form the so called transactions (see [3]). In the followin...