CFP last date
20 May 2024
Reseach Article

Web Mining Techniques in E-Commerce Applications

by Ahmad Tasnim Siddiqui, Sultan Aljahdali
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 69 - Number 8
Year of Publication: 2013
Authors: Ahmad Tasnim Siddiqui, Sultan Aljahdali
10.5120/11864-7648

Ahmad Tasnim Siddiqui, Sultan Aljahdali . Web Mining Techniques in E-Commerce Applications. International Journal of Computer Applications. 69, 8 ( May 2013), 39-43. DOI=10.5120/11864-7648

@article{ 10.5120/11864-7648,
author = { Ahmad Tasnim Siddiqui, Sultan Aljahdali },
title = { Web Mining Techniques in E-Commerce Applications },
journal = { International Journal of Computer Applications },
issue_date = { May 2013 },
volume = { 69 },
number = { 8 },
month = { May },
year = { 2013 },
issn = { 0975-8887 },
pages = { 39-43 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume69/number8/11864-7648/ },
doi = { 10.5120/11864-7648 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:29:43.696506+05:30
%A Ahmad Tasnim Siddiqui
%A Sultan Aljahdali
%T Web Mining Techniques in E-Commerce Applications
%J International Journal of Computer Applications
%@ 0975-8887
%V 69
%N 8
%P 39-43
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Today web is the best medium of communication in modern business. Many companies are redefining their business strategies to improve the business output. Business over internet provides the opportunity to customers and partners where their products and specific business can be found. Nowadays online business breaks the barrier of time and space as compared to the physical office. Big companies around the world are realizing that e-commerce is not just buying and selling over Internet, rather it improves the efficiency to compete with other giants in the market. For this purpose data mining sometimes called as knowledge discovery is used. Web mining is data mining technique that is applied to the WWW. There are vast quantities of information available over the Internet.

References
  1. Data Mining: What is Data Mining?, www. anderson. ucla. edu/faculty/jason. frand/teacher/technologies/palace/datamining. htm
  2. Guandong Xu, Zanchun Yhang, Lin Li, USA:Springer, 2011. Web Mining and Social Networking Techniques and Applications,
  3. J. Palau, M. Montaner, B. Lopez and J. L. de la Rosa. In CIA, pages 137-151, 2004. Collaboration analysis in the recommender system using social networks.
  4. J. M. Kleinberg. In Proc. Of the Ninth Annual ACM-SIAM Symposium on Discrete Algorithms (SODA '98), pages 668-677, 1998 Authoritative sources in a hyperlinked environment.
  5. Zaiane O. , Han J. , In: Workshop on Web Information and Data Management WIDM98, Bethesda, 1998, 9-12. WebML: Querying the World Wide Web for resources and knowledge.
  6. Yang, Q. , Zhang, H. H. and Li, I. T, 2001. Seventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, San Francisco, CA, USA, August 26-29, pp. 473-478. Mining Web logs for prediction models in www caching and prefetching,
  7. Yan, T. W. , Jacobsen, M. Garcia-Molina, H. and Dayal, U. , 1996, Knowledge Discovery from users web page navigation, Seventh International Workshop on Research Issues in Data Engineering, Birmingham, England, aprilie 7-8, pp 20-29.
  8. Berry, M. , Linoff, G. : Data Mining Techniques for Marketing, Sales and Customer Support, John Wiley and Sons, Chichester (1997)
  9. Dunham, M. H. : Data Mining: Introductory and Advanced Topics. Prentice Hall, Pearson Education Inc. (2003)
  10. Prinzie, A. , Van den Poel, D. : Investigating Purchasing Patterns for Financial Services using Markov, MTD and MTDg Models. In: Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 03/213 (2003)
  11. Agrawal, R. , Srikant, R. :Mining sequential patterns, International Conference on Data Engineering(ICDE'95), Taipei, Taiwan, pp. 3-14, martie 1995.
  12. Schechter, S. Krishnan, M. Smith, M. D. : Using path profiles to predict http request, Seventh International World Wide Web Conference, Brisbane, Australia, pp. 457-467, Aprilie, 1998.
  13. Nong, Y. : The handbook of Data Mining, Lawrence Erlbaum Associates, Publishers Mahwah, New Jersey, 2003.
  14. Vercellis, C. : Business Intelligence: Data Mining and Optimization for Decision Making,UK: John Wiley & Sons, 2009
  15. Jiawei Han, Micheline Kamber: Data Mining Concepts and Techniques Second Edition, USA: Elsevier, 2006
  16. Guandong Xu, Zanchun Yhang, Lin Li, Web Mining and Social Networking Techniques and Applications, USA:Springer, 2011
  17. Stephanie Mattingly ,Clickstream Analysis: Both a Business and an Aid in Advertising, Available online: http://cseweb. ucsd. edu/~paturi/cse91/Presents/smattingly. pdf
  18. Web Linkage Mining, Guandong Xu, Yanchun Zhang, Lin Li, http://link. springer. com/chapter/10. 1007%2F978-1-4419-7735-9_5#
  19. http://www. microsoft. com/en-us/sqlserver/solutions-technologies/business-intelligence/predictive-analytics. aspx
  20. http://docs. oracle. com/
  21. http://www. web-datamining. net/content/
  22. http://www. webprofits. com. au/blog/how-does-pagerank-affect-seo-rankings/
  23. B. Berendt, A. Hotho, and G. Stumme, "Towards semantic web mining," Proceedings ofthe International Semantic Web Conference, vol. 2342, pp. 264-278, 2002
  24. A. Rahman, Mehedi Masud, I. Kiringa, and A. El Saddik, A Peer Data Sharing System Combining Schema and Data Level Mappings. Int. Journal of Semantic Computing, Vol. 3(1): 105-129, 2009
  25. Mehedi Masud, Iluju Kiringa, and Hasan Ural. Update Processing in Instance-Mapped Heterogeneous Sources. International Journal of Cooperative Information Systems, Vol 18(3), 2009
  26. Mehedi Masud and Iluju Kiringa. Acquaintance Based Consistency in an Instance-Mapped P2P Data Sharing System During Transaction Processing. 15th Int. Conference on Cooperative Information Systems, Portugal, 2007.
Index Terms

Computer Science
Information Sciences

Keywords

Electronic commerce data mining web mining