Algorithm for Tracing Visitors' On-Line Behaviors for Effective Web Usage Mining

Abstract

behavior identification is an important task in web usage mining. Web usage mining is also called as web log mining. The web logs are mainly used to identify the user behavior. There are so many pattern mining methods which enable this user behavior identification. The preprocessing techniques will maximize the accurate and quality of pattern mining methodologies. In existing algorithms, the preprocessing concepts are applied to calculate the unique user's 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. This paper brings into discussion about the basic concepts of web mining, web usage mining, general data preprocessing, how to preprocess the web data, what are the various existing preprocessing techniques and the proposed VOB algorithm. Keywordspreprocessing methods, Web mining, Web usage mining, Web usage data, Web log.