CFP last date
20 December 2024
Call for Paper
January Edition
IJCA solicits high quality original research papers for the upcoming January edition of the journal. The last date of research paper submission is 20 December 2024

Submit your paper
Know more
The week's pick
Responsive image
SFLA-Based Line Balancing and Task Optimization in Master-Slave Controlled Hanger Transportation Systems for Garment Production

Duc Hoang Nguyen
Random Articles
Reseach Article

Analyzing Users Behavior from Web Access Logs using Automated Log Analyzer Tool

by Neha Goel, C. K. Jha
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 62 - Number 2
Year of Publication: 2013
Authors: Neha Goel, C. K. Jha
10.5120/10054-4643

Neha Goel, C. K. Jha . Analyzing Users Behavior from Web Access Logs using Automated Log Analyzer Tool. International Journal of Computer Applications. 62, 2 ( January 2013), 29-33. DOI=10.5120/10054-4643

@article{ 10.5120/10054-4643,
author = { Neha Goel, C. K. Jha },
title = { Analyzing Users Behavior from Web Access Logs using Automated Log Analyzer Tool },
journal = { International Journal of Computer Applications },
issue_date = { January 2013 },
volume = { 62 },
number = { 2 },
month = { January },
year = { 2013 },
issn = { 0975-8887 },
pages = { 29-33 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume62/number2/10054-4643/ },
doi = { 10.5120/10054-4643 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:10:37.490381+05:30
%A Neha Goel
%A C. K. Jha
%T Analyzing Users Behavior from Web Access Logs using Automated Log Analyzer Tool
%J International Journal of Computer Applications
%@ 0975-8887
%V 62
%N 2
%P 29-33
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Internet is acting as a major source of data. As the number of web pages continues to grow the web provides the data miners with just the right ingredients for extracting information. In order to cater to this growing need a special term called Web mining was coined. Web mining makes use of data mining techniques and deciphers potentially useful information from web data. Web Usage mining deals with understanding the behavior of users by making use of Web Access Logs that are generated on the server while the user is accessing the website. A Web access log comprises of various entries like the name of the user, his IP address, number of bytes transferred timestamp etc. A variety of Log Analyzer tools exist which help in analyzing various things like users navigational pattern, the part of the website the users are mostly interested in etc. The present paper makes use of such log analyzer tool called Web Log Expert for ascertaining the behavior of users who access an astrology website. It also provides a comparative study between a few log analyzer tools available.

References
  1. Brijendra Singh, Hemant Kumar Singh: Web Data Mining Research: A Survey, IEEE, 2010.
  2. G. K. Gupta, Introduction to Data Mining with Case Studies: Web Data Mining, PHI Learning Private Limited, pp. 231-233, 2011.
  3. Theint Aye: Web Log Cleaning for Mining of Web Usage Patterns, IEEE, 2011.
  4. Hillol Kargupta, Anupam Joshi, Krishnamoorthy SivaKumar, Yelena Yesha, Data Mining: Next Generation Challenges and Future Directions: Web Mining – Concepts, Applications and Research Directions, PHI Learning Private Limited, pp. 405-409, 2009.
  5. Navin kr Tyagi ,A. K. Solanki, Manoj Wadhwa : Analysis of Server Log by Web Usage Mining for Website Improvement, IJCSI International Journal of Computer Science Issues, Vol. 7, Issue 4, No 8,pp. 17-21,2010.
  6. L. K. Joshila Grace, V. Maheswari, Dhinaharan Nagamalai: Analysis of Web Logs and Web User In Web Mining, International Journal of Network Security & Its Applications (IJNSA), Vol. 3, No. 1, January 2011.
  7. Xiaozhe Wang, Ajith Abraham, Kate A. Smith: Intelligent web traffic mining and analysis, ELSEVIER Journal of Network and Computing Applications, 2004.
  8. Jian Pei, Jiawei Han, Behzad Mortazavi-asl, and Hua Zhu: Mining Access Patterns Efficiently from Web Logs.
  9. K. R. Suneetha, Dr. R. Krishnamoorthi: Identifying User Behavior by Analyzing Web Server Access Log File in IJCSNS International Journal of Computer Science and Network Security, VOL. 9 No. 4, pp. 327-332, April 2009.
  10. Vic Ciesielski , Anand Lalani : Data Mining of Web Access Logs From an Academic Web Site in Proceedings of the Third International Conference on Hybrid Intelligent Systems (HIS'03): Design and Application of Hybrid Intelligent Systems, pp. 1034-1043, December 2003.
  11. AWStats log file analyzer 7. 1 Documentation , Log AnalyzerComparison:http://awstats. sourceforge. net/docs/awstats_compare. html
  12. http://www. google. com/analytics/
Index Terms

Computer Science
Information Sciences

Keywords

Web Access Logs Web usage Mining Web server Log Analyzer

Powered by PhDFocusTM