Predicting user behavior through sessions using the web log mining

Abstract

It is the method to extract the user sessions from the given log files. Initially, each user is identified according to his/her IP address specified in the log file and corresponding user sessions are extracted. Two types of logs ie., server-side logs and client-side logs are commonly used for web usage and usability analysis. Server-side logs can be automatically generated by web servers, with each entry corresponding to a user request. Client-side logs can capture accurate, comprehensive usage data for usability analysis. Usability is defined as the satisfaction, efficiency and effectiveness with which specific users can complete specific tasks in a particular environment. This process includes 3 stages, namely Data cleaning, User identification, Session identification. In this paper, we are implementing these three phases. Depending upon the frequency of users visiting each page mining is performed. By finding the session of the user we can analyze the user behavior by the time spend on a particular page.