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A Comparative Analysis of Web Usage Mining Techniques

by Paridhi Nigam, Rajesh K. Chakrawarti
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 152 - Number 5
Year of Publication: 2016
Authors: Paridhi Nigam, Rajesh K. Chakrawarti
10.5120/ijca2016911790

Paridhi Nigam, Rajesh K. Chakrawarti . A Comparative Analysis of Web Usage Mining Techniques. International Journal of Computer Applications. 152, 5 ( Oct 2016), 26-29. DOI=10.5120/ijca2016911790

@article{ 10.5120/ijca2016911790,
author = { Paridhi Nigam, Rajesh K. Chakrawarti },
title = { A Comparative Analysis of Web Usage Mining Techniques },
journal = { International Journal of Computer Applications },
issue_date = { Oct 2016 },
volume = { 152 },
number = { 5 },
month = { Oct },
year = { 2016 },
issn = { 0975-8887 },
pages = { 26-29 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume152/number5/26316-2016911790/ },
doi = { 10.5120/ijca2016911790 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:57:22.818291+05:30
%A Paridhi Nigam
%A Rajesh K. Chakrawarti
%T A Comparative Analysis of Web Usage Mining Techniques
%J International Journal of Computer Applications
%@ 0975-8887
%V 152
%N 5
%P 26-29
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Web usage mining is the application of data mining techniques and is used to extract the important data which are present in the web. Nowadays web log mining is a very popular and computationally expensive task. Preprocessing, pattern discovery, and pattern analysis are the major task of web usage mining. In this paper we are presenting an overview of existing algorithms used in pattern discovery phase for mining the frequent item set by designing comparative analysis table i.e. Apriori, K-Apriori, FP growth which are used in pattern discovery phase.

References
  1. Suhasini Parvatikar, Bharti Joshi, “Analysis of User Behavior through Web Usage Mining”, Department of Computing.
  2. R. Kousalya, V Sarvanan, “Improving efficiency of Web Usage Mining using K-Apriori and Fp-Growth Algorithm”
  3. Parth Suthar, Bhavesh Oza Department of Computing Science and engineering, “A Survey of Web Usage Mining Techniques”, L.D College of Engineering, Ahmedabad, Gujarat, India.
  4. Li Chaofeng School of Management, “Research and Development of Data Preprocessing in Web Usage,” South-Central University for Nationalities ,Wuhan 430074, P.R. China.
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  6. Sarita Dalmia, “Wed Mining:survey and Research,”.
  7. B.Santhosh Kumar, K.V Rukmani Department of Computing Science, “ Implementation of Web Usage Mining APRRIORI and FP Growth algorithm”, C. S. I College of Engineering, Ketti- 643215. The Nilgiris.
  8. Jaideep Srivastava , Robert Cooley, Mukund Deshpande, Pang-Ning Tan, “Web Usage Mining: Discovery and Applications of Usage Patterns from Web Data”.
  9. Monika Dhandi, Rajesh Kumar Chakrawarti Department of Computer Science, “ A comprehensive study of Web Usage Mining”, SVITS, Indore.
Index Terms

Computer Science
Information Sciences

Keywords

Web mining Web log mining Apriori K-Apriori FP growth

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