Analyzing Users Behavior from Web Access Logs using Automated Log Analyzer Tool

Abstract

Internet is acting as a major source of data. As the number of web pages continues to grow the web provides the data miners with just the right ingredients for extracting information. In order to cater to this growing need a special term called Web mining was coined. Web mining makes use of data mining techniques and deciphers potentially useful information from web data. Web Usage mining deals with understanding the behavior of users by making use of Web Access Logs that are generated on the server while the user is accessing the website. A Web access log comprises of various entries like the name of the user, his IP address, number of bytes transferred timestamp etc. A variety of Log Analyzer tools exist which help in analyzing various things like users navigational pattern, the part of the website the users are mostly interested in etc. The present paper makes use of such log analyzer tool called Web Log Expert for ascertaining the behavior of users who access an astrology website. It also provides a comparative study between a few log analyzer tools available.