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Web Usage Mining for Discovery and Evaluation of Online Navigation Pattern Prediction

by Pradnya Mehta, Shailaja B. Jadhav, R. B. Joshi
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 91 - Number 4
Year of Publication: 2014
Authors: Pradnya Mehta, Shailaja B. Jadhav, R. B. Joshi
10.5120/15870-4815

Pradnya Mehta, Shailaja B. Jadhav, R. B. Joshi . Web Usage Mining for Discovery and Evaluation of Online Navigation Pattern Prediction. International Journal of Computer Applications. 91, 4 ( April 2014), 23-26. DOI=10.5120/15870-4815

@article{ 10.5120/15870-4815,
author = { Pradnya Mehta, Shailaja B. Jadhav, R. B. Joshi },
title = { Web Usage Mining for Discovery and Evaluation of Online Navigation Pattern Prediction },
journal = { International Journal of Computer Applications },
issue_date = { April 2014 },
volume = { 91 },
number = { 4 },
month = { April },
year = { 2014 },
issn = { 0975-8887 },
pages = { 23-26 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume91/number4/15870-4815/ },
doi = { 10.5120/15870-4815 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:11:54.035587+05:30
%A Pradnya Mehta
%A Shailaja B. Jadhav
%A R. B. Joshi
%T Web Usage Mining for Discovery and Evaluation of Online Navigation Pattern Prediction
%J International Journal of Computer Applications
%@ 0975-8887
%V 91
%N 4
%P 23-26
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Web mining is combination of two activated research areas Data Mining and World Wide Web. Web mining is used for mining the interested knowledge from World Wide Web. Web usage mining is used to discover the user access patterns from web server log files. The first step of web usage mining called as data pre-processing used for gaining an accurate web log mining results and good quality input data. The session identification is accomplished by time oriented heuristics. The focus is on referrer log which will which contain information about referrer page of the current page. An efficient approach for discovery of navigation pattern can be done by density based clustering algorithm. An online navigation pattern prediction is proposed by use of K nearest neighbor algorithm along with inverted index concept. The prediction accuracy of patterns can be increased by modifying TF-IDF values to include time spent on page.

References
  1. Abdelghani Guerbas, Omar Addam, Omar Zaarour, Mohamad Nagi, Ahmad Elhajj, Mick Ridley,Reda Alhajj"Effective web log mining and online navigational pattern prediction"(2013)
  2. Juan D. Velásquez "Web mining and privacy concerns: Some important legal issues to be consider before applying any data and information extraction technique in web-based environments"(2013)
  3. Pawe? Weichbroth Mieczys?aw Owoc Micha? Pleszkun "Web User Navigation Patterns Discovery from WWW Server Log Files " (2012).
  4. Tasawar Hussain, Dr. Sohail Asghar, Dr. Nayyer Masood "Web Usage Mining: A Survey on Preprocessing of Web Log File"(2012)
  5. Theint Theint Aye "Web Log Cleaning for Mining of Web Usage Patterns" (2011)
  6. Quanshu Zhou1,"Performance Analysis of Web Applications Based on User Navigation "
  7. A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise Martin Ester, Hans-Peter Kriegel, J&g Sander, Xiaowei Xu
  8. Renáta Iváncsy " Different Aspects of Web Log Mining "(2010)
  9. Lara D. Catledge1 "Characterizing Browsing Strategies in the World-Wide (2010)
  10. Bettina Berendt Measuring the accuracy of sessionizer for web usage analysis
  11. M Agosti " Web Log Mining: A Study of User Sessions "(2007)
  12. B. Berendt, B. Mobasher, M. Nakagawa, M. Spiliopoulou, The impact of site structure and user environment on session reconstruction in web usage analysis, Webkdd 2002 – Mining Web Data For Discovering Usage patterns and Profiles (2003) 159–179.
  13. Prof. Bhupendra Verma1 "Single Level Algorithm: An Improved Approach for Extracting User Navigational Patterns To Improve Website Effectiveness" (2010)
  14. Web Mining for Web Personalization MAGDALINI EIRINAKI and MICHALIS VAZIRGIANNIS(2003)
  15. B. Mobasher, H. Dai, T. Luo, M. Nakagawa, Discovery and evaluation of aggregate usage profiles for web personalization, Data Mining and Knowledge Discovery (2002) 61–82.
  16. H. Zhang, A. Ghorbani, The reconstruction of user sessions from a server log using improved time-oriented heuristics, in: Second Annual Conference on Communication Networks and Services Research, Proceedings, 2004, pp. 315– 322
  17. Analia Lourenco,Catching web crawlers in ac
  18. Khalid Hammouda, Prof. Fakhreddine Karray,?A Comparative Study of Data Clustering Techniques? University of Waterloo, Ontario, Canada N2L 3G1
  19. Xin Wang and Howard J. Hamilton " A Comparative Study of Two Density-Based Spatial Clustering Algorithms for Very Large Datasets"
  20. Robert walker Cooley "Web usage mining: Discovery and application of interesting patterns from web data "(2000)
  21. Qingtian Han1" Study on Web Mining Algorithm Based on Usage Mining"
  22. M. Ankerst, M. Breunig, H. Kriegel, J. Sander, OPTICS: ordering points to identify the clustering structure, Sigmod Record 28 (2) (1999) 49–60.
Index Terms

Computer Science
Information Sciences

Keywords

Web usage mining User session analysis Log File Analysis Indexing and cluster analysis

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