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Reseach Article

Web Log Mining using K-Apriori Algorithm

by Ashok Kumar D, Loraine Charlet Annie M.c.
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 41 - Number 11
Year of Publication: 2012
Authors: Ashok Kumar D, Loraine Charlet Annie M.c.
10.5120/5584-7820

Ashok Kumar D, Loraine Charlet Annie M.c. . Web Log Mining using K-Apriori Algorithm. International Journal of Computer Applications. 41, 11 ( March 2012), 16-20. DOI=10.5120/5584-7820

@article{ 10.5120/5584-7820,
author = { Ashok Kumar D, Loraine Charlet Annie M.c. },
title = { Web Log Mining using K-Apriori Algorithm },
journal = { International Journal of Computer Applications },
issue_date = { March 2012 },
volume = { 41 },
number = { 11 },
month = { March },
year = { 2012 },
issn = { 0975-8887 },
pages = { 16-20 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume41/number11/5584-7820/ },
doi = { 10.5120/5584-7820 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:29:18.554732+05:30
%A Ashok Kumar D
%A Loraine Charlet Annie M.c.
%T Web Log Mining using K-Apriori Algorithm
%J International Journal of Computer Applications
%@ 0975-8887
%V 41
%N 11
%P 16-20
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Web log mining is a data mining technique which extracts useful information from the World Wide Web's (WWW) client usage details. Automated data gathering has resulted in extremely large information about web access and it can be represented in binary form. A novel method called K-Apriori algorithm is proposed here, to find the frequently accessed web pages from the very large binary weblog databases. Experimental results show that the proposed method has shows higher performance in terms of objectivity and subjectivity.

References
  1. Raymond Kosala and Hendrik Blockeel. 2000, "Web Mining Research: A Survey", ACM SIGKDD.
  2. Sanjay Kumar Madria, Sourav S Bhowmick, Ng W. K. and Lim E. P. 1999, "Research Issues in Web Data Mining", Springer.
  3. Qingyu Zhang and Richard S. Segall. 2008, "Web Mining: A Survey Of Current Research, Techniques, And Software", In International Journal of Information Technology and Decision Making, Volume: 07, Issue: 04, pp. 683-720.
  4. Agrawal R and Srikant R . 1984. " Fast algorithms for mining association rules", In Proceedings of the 20th VLDB conference, pp. 487–499.
  5. Borgelt C. 2003. "Efficient Implementations of Apriori and Eclat", Proceedings of the IEEE ICDM Workshop on Frequent Itemset Mining Implementations (FIMI), Melbourne, Florida.
  6. Han J, Pei H, and Yin Y. 2000. "Mining Frequent Patterns without Candidate Generation", In Proc. Conf. on the Management of Data SIGMOD, Dallas, TX. ACM Press, New York, USA.
  7. Liu J,Pan Y,Wang K, andHan J. 2002. "Mining Frequent Item Sets by Opportunistic Projection", Proceedings of ACM SIGKDD, Edmonton, Alberta, Canada.
  8. Gopalan R. P and Sucahyo Y. G. 2004. "High Performance Frequent Pattern Extraction using Compressed FPTrees", Proceedings of SIAM International Workshop on High Performance and Distributed Mining (HPDM),Orlando, USA.
  9. Han J and Kamber M. 2001. "Data Mining: Concepts and Techniuqes", Morgan Kaufmann Publishers, San Francisco, CA.
  10. Wanjun Yu, Xiaochun Wang, Fangyi Wang, Erkang Wang and Bowen Chen, 2008. "The research of improved apriori algorithm for mining association rules", 11th IEEE International Conference on Communication Technology, pp. 513 - 516.
  11. Frederic Garcia Becerro. 2007, "Report on Wiener filtering", Image Analysis, Vibot. [Online] http://eia. udg. edu/~fgarciab/.
  12. McQueen J. 1967. "Some methods for classification and analysis of multivariate observations", In Proc. of 5th Berkeley Symp Mathematics,statistics and probability, pp. 281-296.
  13. Tapas Kanungo, David M. Mount, Nathan S. Netanyahu, Christine D. Piatko, Ruth Silverman, and Angela Y. Wu, 2002. "An Efficient k-Means Clustering Algorithm: Analysis and Implementation", IEEE Transactions on Pattern Analysis and Machine Intelligence", pp. 881-892.
Index Terms

Computer Science
Information Sciences

Keywords

Wiener Transformation K-apriori Web Mining