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

International Journal of Computer Applications
© 2014 by IJCA Journal
Volume 87 - Number 3
Year of Publication: 2014
S. Uma Maheswari
S. K. Srivatsa

Uma S Maheswari and S K Srivatsa. Article: Algorithm for Tracing Visitors On-Line Behaviors for Effective Web Usage Mining. International Journal of Computer Applications 87(3):22-28, February 2014. Full text available. BibTeX

	author = {S. Uma Maheswari and S. K. Srivatsa},
	title = {Article: Algorithm for Tracing Visitors On-Line Behaviors for Effective Web Usage Mining},
	journal = {International Journal of Computer Applications},
	year = {2014},
	volume = {87},
	number = {3},
	pages = {22-28},
	month = {February},
	note = {Full text available}


User 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.


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