Adapting the right Web pages to the right users

Abstract

With the explosive use of the Internet, there is an ever-increasing volume of Web usage data being generated and warehoused in numerous successful Web sites. Analyzing Web usage data can help Web developers to improve the organization and presentation of their Web sites. Considering the fact that mining for patterns and rules in market basket data is well studied in data mining field, we provide a mapping approach, which can transform Web usage data into the form like market basket data. Using our model, all the methods developed by data mining research groups can be directly applied on Web usage data without much change. Existing methods for knowledge discovery in Web logs are restricted by the difficulty of getting the complete and reliable Web usage data and effectively identifying user sessions using current Web server log mechanism. The problem is due to Web caching and the existence of proxy servers. As an effort to remedy this problem, we built our own Web server log mechanism that can effectively capture user access behaviour and will not be deliberately bypassed by proxy servers and end users.