Tracing Visitors Online Behaviors by Using VOB Algorithm for Effective Web Usage Mining

Web mining can be broadly defined as discovery and analysis of useful information from the World Wide Web. It can also be defined as automatic discovery of patterns in clickstreams and associated data collected or generated as a result of user interactions with one or more Web sites. The main important goal of Web Usage mining is to analyze the behavioral patterns and profiles of users interacting with a Web site. Web usage mining also called web log mining. Web mining is one of the techniques of Data mining. The main purpose of this paper is to identify the user behavior and pattern by using basic concept of Web mining, Web Usage mining, general data preprocessing, what are the various existing preprocessing techniques and the proposed Visitors Online Behavior VOB algorithm. . There are several pattern mining methods which enable user behavior identification. In existing algorithms, the preprocessing concepts are applied to calculate the unique users count, to minimize the log file size and to identify the sessions. The newly proposed algorithm is Visitors Online Behavior (VOB) which identifies user behavior, creates user cluster and page cluster, and tells the most popular web page and least popular web page.