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Reseach Article

Predicting the Behaviour and Interest of the Website Users through Web Log Analysis

by Arvind K. Sharma, P. C. Gupta
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 64 - Number 7
Year of Publication: 2013
Authors: Arvind K. Sharma, P. C. Gupta
10.5120/10646-5404

Arvind K. Sharma, P. C. Gupta . Predicting the Behaviour and Interest of the Website Users through Web Log Analysis. International Journal of Computer Applications. 64, 7 ( February 2013), 17-23. DOI=10.5120/10646-5404

@article{ 10.5120/10646-5404,
author = { Arvind K. Sharma, P. C. Gupta },
title = { Predicting the Behaviour and Interest of the Website Users through Web Log Analysis },
journal = { International Journal of Computer Applications },
issue_date = { February 2013 },
volume = { 64 },
number = { 7 },
month = { February },
year = { 2013 },
issn = { 0975-8887 },
pages = { 17-23 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume64/number7/10646-5404/ },
doi = { 10.5120/10646-5404 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:15:45.764480+05:30
%A Arvind K. Sharma
%A P. C. Gupta
%T Predicting the Behaviour and Interest of the Website Users through Web Log Analysis
%J International Journal of Computer Applications
%@ 0975-8887
%V 64
%N 7
%P 17-23
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Web mining is a hot research area of many researchers. Web mining techniques have been widely used to discover interesting and frequent user navigation patterns from the web server logs. The aim of this work is to apply web mining techniques for discovering user's behaviour and interest for an educational institution website usage to reveal previously unknown interesting patterns extracted in order to recommend possible measures for further improvement of the Website. In this paper the web user access and server usage patterns have been analyzed and daily, weekly, monthly web metrics such as number of visits, pages, files, hits and sites have been investigated. An attempt has been made to predict the behaviour and interest of the website users.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Web server logs Web log analysis AWStats