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Constraint-based Web Log Mining for Analyzing Customers’ Behaviour

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International Journal of Computer Applications
© 2010 by IJCA Journal
Number 10 - Article 2
Year of Publication: 2010
Authors:
Anagha Shastri
Dipti Patil
V.M.Wadhai
10.5120/1621-2180

Anagha Shastri, Dipti Patil and V.M.Wadhai. Article:Constraint-based Web Log Mining for Analyzing Customers Behaviour. International Journal of Computer Applications 11(10):7–11, December 2010. Published By Foundation of Computer Science. BibTeX

@article{key:article,
	author = {Anagha Shastri and Dipti Patil and V.M.Wadhai},
	title = {Article:Constraint-based Web Log Mining for Analyzing Customers Behaviour},
	journal = {International Journal of Computer Applications},
	year = {2010},
	volume = {11},
	number = {10},
	pages = {7--11},
	month = {December},
	note = {Published By Foundation of Computer Science}
}

Abstract

Analysis of Web logs is one of the important challenges to provide Web intelligent services. Association rule mining algorithms are used widely to track users' web behaviour. Due to large amount of data many times the rules formed by these algorithms are very long and redundant. Recently Constraint-based mining approaches have received attention to deal with these big and redundant association rules. In this paper we discuss the Constraint based web mining approach used to reduce the size of association rules derived from Web log. The approach proves effective in reducing the overlap of information and also improves the efficiency of mining tasks. Constraint-based mining enables users to concentrate on mining their interested association rules instead of the complete set of association rules.

Reference

  • R. Cooley, J. Srivastava, and B. Mobasher, “Web mining: Information and pattern discovery on the World Wide Web”. In 9th IEEE International Conference on Tools with Artificial Intelligence (ICTAI’97), November 1997.
  • M. Eirinaki and M. Vazirgiannis, “Web mining for web personalization”. In ACM Trans. Inter. Tech., vol. 3, no. 1, pp. 1-27, 2003
  • Mathia Gery, Hatem Haddad, “Evaluation of Web Usage Mining Approaches for User’s Next Request Prediction”. In WIDM ’03, ACM November 2003.
  • R. Cooley, B. Mobasher, and J. Srivastava, “Data preparation for mining world wide web browsing patterns” In Knowledge and Information Systems, vol. 1, no. 1, pp. 5-32, 1999.
  • Xin Chen and Yi-fang Brook Wu, “Web Mining from Competitors’ Websites”, Research track poster, New Jersey Institute of Technology
  • W. Yang, Yuefeng Li, Yue Xu, Hang Liu, “Rough Set Model for Constraint-based Multi-dimensional Association Rule” In journal Software Engineering and Data Communication of Queensland University of Technology, Brisban.
  • R.T.Ng, L.V.S. Lakshmanan, J. Han, A. Pang, “Exploratory Mining and Pruning Optimizations of Constrained Associations Rules”. In Proceedings of ACM-SIGMOD, 1998, pp. 13-24.
  • Rajendra K.Gupta and Dev Prakash Agarwal, “Improving the performance of Association Rule Mining Algorithms by Filtering Insignificant Transactions dynamically”, Asian Journal of Information Management, pp.7-17. 2009 Academic Journals Inc.
  • V.Umarani, Dr.M. Punithavalli, “A Study on Effective Mining of Association Rules from Huge Databases”, IJCSR International Journal of Computer Science and Research, Vol 1 Issue 1, 2010