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Reseach Article

Applying Web Usage Mining to a University Website Access Domain

by Nirali Honest, Bankim Patel, Atul Patel
International Journal of Applied Information Systems
Foundation of Computer Science (FCS), NY, USA
Volume 2 - Number 9
Year of Publication: 2012
Authors: Nirali Honest, Bankim Patel, Atul Patel
10.5120/ijais12-450403

Nirali Honest, Bankim Patel, Atul Patel . Applying Web Usage Mining to a University Website Access Domain. International Journal of Applied Information Systems. 2, 9 ( June 2012), 7-14. DOI=10.5120/ijais12-450403

@article{ 10.5120/ijais12-450403,
author = { Nirali Honest, Bankim Patel, Atul Patel },
title = { Applying Web Usage Mining to a University Website Access Domain },
journal = { International Journal of Applied Information Systems },
issue_date = { June 2012 },
volume = { 2 },
number = { 9 },
month = { June },
year = { 2012 },
issn = { 2249-0868 },
pages = { 7-14 },
numpages = {9},
url = { https://www.ijais.org/archives/volume2/number9/188-0403/ },
doi = { 10.5120/ijais12-450403 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2023-07-05T10:44:00.012964+05:30
%A Nirali Honest
%A Bankim Patel
%A Atul Patel
%T Applying Web Usage Mining to a University Website Access Domain
%J International Journal of Applied Information Systems
%@ 2249-0868
%V 2
%N 9
%P 7-14
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Web Usage Mining (WUM) is the process of taking out interesting behavior patterns that allow analyzing uses by the website administrator. In this paper we discuss the impact of developing the WUM process according to the requirements specific to the access of University website. WUM becomes a important aspect in today's era because the quantity of data is continuously increasing, the data resulted as part of web traffic comes from different sources and different format so issues related to integration and analyzing this heterogeneous and complex data are required before conducting any WUM analysis. Apart from these factors (large size of data and Heterogeneous structure) the three steps of WUM process are not coordinated to create a coherent and unique process. With these main concerns we decide to work for University website management domain and prepare a new reactive approach which uses the web usage data . site topology, academic calendar of university, in order to produce more specific process and results for University environment.

References
  1. HAN Jia-Wei, MENG Xiao-Feng, WANG Jing etc. Research on Web Mining. Journal of Computer ResearchLkDevelopment, 2001,38(4): 405-414.
  2. Bing Liu , Web Content Mining ,The 14th International World Wide Web Conference (WWW-2005),May 10-14, 2005, Chiba, Japan. ,
  3. Jaideep Srivastava, Robert Cooley, Mukund Deshpande, Pang-Ning Tan , "Web Usage Mining: Discovery and Applications of Usage Patterns from Web Data ", ACM SIGKDD Explorations, Volume 1, Issue 2 , Jan 2000.
  4. Doru Tanasa and Brigitte Trousse, " Advanced Data Preprocessing for Intersites Web Usage Mining ", IEEE Computer Society, March/April, 2004.
  5. Fang Yuan, Li-Juan Wang, Ge Yu, " Study on Data Preprocessing Algorithm in Web Log Mining ", Proceedings of the Second International Conferences on Machine Learning and Cybernetics, Xi'an, 2-5 November 2003.
  6. Mohd Helmy Abd Wahab, Mohd Norzali Haji Mohd, et. Al, "Data Pre-processing on Web Server Logs for Generalized Association Rules Mining Algorithm" , World Academy of Science, Engineering and Technology, 2008.
  7. K. R. Suneetha, Dr. R. Krishnamoorthi, " Identifying User Behavior by Analyzing Web Server Access Log File", International Journal of Computer Science and Network Security, Vol. 9 No. 4, April 2009.
  8. Ms. Dipa Dixit and Ms M Kiruthika, " Preprocessing of web logs" , International Journal on Computer Science and Engineering, Vol. 02, No. 07,2010, 2447-2452.
  9. Carlos G. Marquardt, Karin Becker and Duncan D. Ruiz, " A pre-processing tool for Web Usage Mining in the Distance Education Domain", Proceedings of the International Database Engineering and Applications Symposium ( IDEAS'04) IEEE, 2004.
  10. Khasawneh, N. and C. -C. Chan (2006). Active User-Based and Ontology-Based Web Log Data Preprocessing for Web Usage Mining. Proceedings of the 2006 IEEE/WIC/ACM International Conference on Web Intelligence (WI 2006 Main Conference Proceedings) (WI'06) 0-7695-2747-7/06 © 2006.
  11. Pabarskaite, Z. (2002). Implementing Advanced Cleaning and End-User Interpretability Technologies in Web Log Mining. 24th Int. Conf. information Technology Interfaces /TI 2002, June 24-27, 2002, Cavtat, Croatia.
  12. Han, J. and M. Kamber (2006). Data Mining: Concepts and Techniques. A. Stephan. San Francisco,, Morgan Kaufmann Publishers is an imprint of Elsevier.
  13. Master Page Architecture and working, found at, http://msdn. microsoft. com/en-us/library/wtxbf3hh. aspx
  14. B. Berendt and M. Spiliopoulou, Analysis of Navigation Behaviour in Web Sites Integrating Information Systems. VLDB Journal 9, 2000.
  15. B. Mobasher, et. al, Automatic Personalization based on Web Usage Mining. In Communications of the ACM, 8, 2000.
  16. M. Spiliopoulou, L. C. Faulstich, and K. Winkler, A Data Miner analysing the Navigational Behaviour of Web Users. In: Proc. of Workshop on Machine Learning in User Modelling , 1999.
  17. O. R. Zaïane, Web Usage Mining for a Better Web-Based Learning Environment. Department of Computing Science University of Alberta Edmonton, Alberta, Canada, 2001.
  18. O. R. Zaïane and J. Luo, Towards Evaluating Learners' Behaviour in a Web-Based Distance Learning Environment. In: Proceedings IEEE ICALT 2001, Madison, USA. 2001.
  19. R. Cooley, et. al. , Web Mining: Information and Pattern Discovery on the World Wide Web. 1997. Proc. IEEE Intl. Conf. Tools with AI, Newport Beach, CA, pp. 558-567, 1997.
  20. R. Cooley, B. Mobasher, and J. Srivastava, Data Preparation for Mining World Wide Web Browsing Patterns. Journal of Knowledge and Information Systems, (1), 1999.
  21. Master Page Information, found at , http://www. w3schools. com/aspnet/aspnet_masterpages. asp
  22. Image Reference and path of the image http://i. msdn. microsoft. com/dynimg/IC147301. gif
Index Terms

Computer Science
Information Sciences

Keywords

Master Page Concept Data Pre-processing Academic Events