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Frequent Pattern Mining of Web Log Files Working Principles

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2017
Authors:
K. Suguna, K. Nandhini
10.5120/ijca2017912642

K Suguna and K Nandhini. Frequent Pattern Mining of Web Log Files Working Principles. International Journal of Computer Applications 157(3):1-5, January 2017. BibTeX

@article{10.5120/ijca2017912642,
	author = {K. Suguna and K. Nandhini},
	title = {Frequent Pattern Mining of Web Log Files Working Principles},
	journal = {International Journal of Computer Applications},
	issue_date = {January 2017},
	volume = {157},
	number = {3},
	month = {Jan},
	year = {2017},
	issn = {0975-8887},
	pages = {1-5},
	numpages = {5},
	url = {http://www.ijcaonline.org/archives/volume157/number3/26808-2017912642},
	doi = {10.5120/ijca2017912642},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

Frequent pattern mining plays a major role in mining of web log files. Web usage mining is the one of the web mining process that involves application of mining techniques to web server logs to extract the behavior of users. A web usage mining consists of three important phases: data preprocessing, patterns discovery and pattern analysis. In data preprocessing phase the unwanted data are removed and that are structured into necessary format for mining. It enables the user to translate the unprocessed data which is from server log files into useful data. The appropriate analysis of a web server log proves that the websites efficiently from the administrative and users’ prospective. Preprocessing results also more useful for the next phases of web usage mining.

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Keywords

World wide web, Preprocessing, Web usage mining and web server logs.