The usage analysis of a Web site based on the extracted sequential patterns is often limited by the low support of these patterns. That is mainly due to the great diversity of the pages and behaviors. However, it is possible to group the majority of these pages in various categories during a preprocessing. Then, using these categories, rather than the URL, will allow us to discover "generic" be...

Web usage mining is a main research area in Web mining focused on learning about Web users and their interactions with Web sites. The motive of mining is to find users’ access models automatically and quickly from the vast Web log data, such as frequent access paths, frequent access page groups and user clustering. Through web usage mining, the server log, registration information and other rel...

-World Wide Web provides abundance of information for the Internet users and is a huge repository of web pages and links. The growth of web is tremendous as approximately one million pages are added daily. Web logs record users’ accesses. Because of the tremendous usage of web , the web log files are growing at a faster rate and the size is becoming huge. Web data mining is the application of d...

Web usage mining is a main research area in Web mining focused on learning about Web users and their interactions with Web sites. The motive of mining is to find users’ access models automatically and quickly from the vast Web log data, such as frequent access paths, frequent access page groups and user clustering. Through web usage mining, the server log, registration information and other rel...

Analysis and discovery of useful information from World Wide Web poses a phenomenal challenge to the researcher. In this area, the phenomenon of retrieving valuable information by adopting the data mining techniques is called web mining. Web mining is classified into following five sub tasks: 1) Resource finding, 2) Information Selection and Pre-processing, 3) Generalization, 4) Analysis and 5)...

The rising popularity of electronic commerce makes data mining an indispensable technology for business competitiveness. The World Wide Web provides abundant raw data in the form of web access logs, web transaction logs and web user profiles. Without data mining tools, it is impossible to make any sense of such massive data. In this paper, we focus on web usage mining because it deals most appr...

With the increase of large web sites which have complex link structures, web access logs have caught attention as a clue for web site administrators to understand user’s needs and demands. While conventional statistical analysis is used for most of the cases, web usage mining is an emerging attempt to apply data-mining based technique to web access log analyses. However, statistical and data-mi...

Existing web usage mining techniques focus only on discovering knowledge based on the statistical measures obtained from the static characteristics of web usage data. They do not consider the dynamic nature of web usage data. In this paper, we present an algorithm called Cleopatra (CLustering of EvOlutionary PAtTeRn-based web Access sequences) to cluster web access sequences (WASs) based on the...

Existing approaches to Web personalization often rely heavily on explicit and subjective user input resulting in static profiles which are prone to biases. In this paper we present a usagebased Web personalization system, called WebPersonalizer, drawing heavily upon Web mining techniques, making the personalization process automatic, and dynamic. The system architecture separates the offline ta...

With the possibility of world wide access current Web applications have an almost unlimited amount of potential users. Methods of data mining can be used to classify the user groups and to learn from their behavior. With the collected information changes and optimizations can be applied to the Web application to hit the users requirements. One already established method for data mining is Web u...