Pattern discovery and users classification through web usage mining

Web usage mining is a special area of web mining which is based upon the discovery and analysis of web usage patterns from web logs so as to effectively and efficiently serve the needs of the users visiting the websites. The main focus of this paper is on doing users classification on the basis of discovered patterns from web logs. Our proposed framework is based on three steps. In the first step, preprocessing is done to remove useless data from web log file so as to reduce its size. In the second step, this cleaned log file is used for discovering usage patterns. Finally, the discovered patterns lead to the classification of users: on the basis of countries; on the basis of direct entry to the site or referred by the other site; on the basis of ti me of access, i.e., either different seasons or different months or different days. This information can then be used by the website administrators for efficient administration and personalization of their websites and thus the specific needs of specific communities of users can be fulfilled and so the profit can be increased.