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Mining Access Patterns Using Clustering

by Mrs. Dipa Dixit, Mrs. Kiruthika M
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 4 - Number 11
Year of Publication: 2010
Authors: Mrs. Dipa Dixit, Mrs. Kiruthika M
10.5120/868-1218

Mrs. Dipa Dixit, Mrs. Kiruthika M . Mining Access Patterns Using Clustering. International Journal of Computer Applications. 4, 11 ( August 2010), 22-26. DOI=10.5120/868-1218

@article{ 10.5120/868-1218,
author = { Mrs. Dipa Dixit, Mrs. Kiruthika M },
title = { Mining Access Patterns Using Clustering },
journal = { International Journal of Computer Applications },
issue_date = { August 2010 },
volume = { 4 },
number = { 11 },
month = { August },
year = { 2010 },
issn = { 0975-8887 },
pages = { 22-26 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume4/number11/868-1218/ },
doi = { 10.5120/868-1218 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T19:52:51.147164+05:30
%A Mrs. Dipa Dixit
%A Mrs. Kiruthika M
%T Mining Access Patterns Using Clustering
%J International Journal of Computer Applications
%@ 0975-8887
%V 4
%N 11
%P 22-26
%D 2010
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Web usage mining is an application of data mining techniques to discover usage patterns from web data, in order to understand and better serve the needs of web based application. The aim of this paper is to discuss about a system proposed which would perform clustering of user sessions extracted from the web logs.HTML links are extracted from these web logs for each user which constitutes the dataset. Clustering is then performed on these datasets based on the key attributes to partition the users into several homogenous groups such that similar user access patterns belong to the same cluster. Implementation and the results are also discussed.

References
  1. Cooley, R. Mobasher, B. and Srivastave, J. “Web Mining: Information and Pattern Discovery on the World Wide Web” (1997) In Proceedings of the 9th IEEE ICTAI Conference, pp. 558-567, Newport Beach, CA, USA.
  2. I-Hsien Ting, Chris Kimble,Daniel Kudenko, “Applying Web Usage Mining Techniques to Discover Potential Browsing Problems of Users”, Department of Computer Science, the University of York, Seventh IEEE International Conference on Advanced Learning Technologies,2007.
  3. Margaret H Dunham, “Data mining introductory and advanced topics” 5th Ed.
  4. Jiawei Han and Micheline Kamber, “Data mining: concepts and techniques”.
  5. Jian Pei,Jiawi, HanBehzad Mortazavi-asl and Hua Zhu Simon Fraser ,“Mining access patterns efficiently from web logs” by University,Canada.
  6. Yan LIa,b, Boqin FENGa, Qinjiao MAOa, Xi' an Jiaotong, Shaanxi, “Research on Path Completion Technique in Web Usage Mining” University of Technology, China.
Index Terms

Computer Science
Information Sciences

Keywords

Web Usage mining Access Patterns classification

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