A MapReduce-Based User Identification Algorithm in Web Usage Mining

Abstract

This article contends that in the booming era of information, analysing users' navigation behaviour is an important task. User identification is considered as one of the important and challenging tasks in the data preprocessing phase of the Web usage mining process. There are three important issues with the reactive strategies of User identification methods that need to be focused: the first is dealing of sharing IP address problem in a proxy server environment, the second is distinguishing users from Web robots, and the third is dealing with huge datasets efficiently. In this article, authors have developed a MapReduce-based User identification algorithm that deals with the above mentioned three issues related to user identification methods. Moreover, the experiment on the real web server log shows the effectiveness and efficiency of the developed algorithm.