CFP last date
20 January 2025
Call for Paper
February Edition
IJCA solicits high quality original research papers for the upcoming February edition of the journal. The last date of research paper submission is 20 January 2025

Submit your paper
Know more
The week's pick
Responsive image
SFLA-Based Line Balancing and Task Optimization in Master-Slave Controlled Hanger Transportation Systems for Garment Production

Duc Hoang Nguyen
Random Articles
Reseach Article

Knowledge Discovery from Web Usage Data: An Efficient Implementation of Web Log Preprocessing Techniques

by Shivaprasad G., N.v. Subba Reddy, U. Dinesh Acharya
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 111 - Number 13
Year of Publication: 2015
Authors: Shivaprasad G., N.v. Subba Reddy, U. Dinesh Acharya
10.5120/19600-1451

Shivaprasad G., N.v. Subba Reddy, U. Dinesh Acharya . Knowledge Discovery from Web Usage Data: An Efficient Implementation of Web Log Preprocessing Techniques. International Journal of Computer Applications. 111, 13 ( February 2015), 27-32. DOI=10.5120/19600-1451

@article{ 10.5120/19600-1451,
author = { Shivaprasad G., N.v. Subba Reddy, U. Dinesh Acharya },
title = { Knowledge Discovery from Web Usage Data: An Efficient Implementation of Web Log Preprocessing Techniques },
journal = { International Journal of Computer Applications },
issue_date = { February 2015 },
volume = { 111 },
number = { 13 },
month = { February },
year = { 2015 },
issn = { 0975-8887 },
pages = { 27-32 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume111/number13/19600-1451/ },
doi = { 10.5120/19600-1451 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:47:48.633535+05:30
%A Shivaprasad G.
%A N.v. Subba Reddy
%A U. Dinesh Acharya
%T Knowledge Discovery from Web Usage Data: An Efficient Implementation of Web Log Preprocessing Techniques
%J International Journal of Computer Applications
%@ 0975-8887
%V 111
%N 13
%P 27-32
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Web Usage Mining (WUM) refers to extraction of knowledge from the web log data by application of data mining techniques. WUM generally consists of Web Log Preprocessing, Web Log Knowledge Discovery and Web Log Pattern Analysis. Web Log Preprocessing is a major and complex task of WUM. Elimination of noise and irrelevant data, thereby reducing the burden on the system leads to efficient discovery of patterns by further stages of WUM. In this paper, Web Log Preprocessing Methods to efficiently identify users and user sessions have been implemented and results have been analyzed.

References
  1. Supriya Kumar De and P. Radha Krishna, 2004, "Clustering web transactions using rough approximation, Fuzzy Sets and Systems", Vol. 148, Science Direct, 131–138.
  2. Nitya P. and Sumathi P. , 2012, "Novel pre-processing technique for web log mining by removing global noise and web robots", National Conference on Computing and Communication Systems (NCCCS), IEEE, 1-5.
  3. G. Arumugam and S. Suguna, 2009, "Optimal Algorithms for Generation of User Session Sequences Using Server Side Web User Logs", International Conference on Network and Service Security, IEEE, 1- 6.
  4. Sudheer Reddy K. , Kantha Reddy M. and Sitaramulu V. , 2013, "An effective data preprocessing method for Web Usage Mining", International Conference on Information Communication and Embedded Systems (ICICES), IEEE, 7-10.
  5. Aye T. T. , 2011, "Web log cleaning for mining of web usage patterns", Third International Conference on Computer Research and Development (ICCRD), Vol. 2, IEEE, 490-494.
  6. K Sudheer Reddy, G. Partha Saradhi Varma and I. Ramesh Babu, 2012, "Preprocessing the Web Server Logs – An illustrative approach for effective usage mining", ACM SIGSOFT Software Engineering Notes, Vol. 37. No. 3, 1-5.
  7. G. Shiva Prasad, N. V. Subba Reddy, and U. Dinesh Acharya, 2010, "Knowledge Discovery from Web Usage Data: A Survey of Web Usage Pre-processing Techniques", Proc. of International Conference on Recent Trends in Business Administration and Information Processing (BAIP 2010), Communications in Computer and Information Science, Vol. 70, Springer Berlin Heidelberg, 505-507.
  8. Brijesh Bakariya, Krishna K. Mohbey and G. S. Thakur, 2013, "An Inclusive Survey on Data Preprocessing Methods Used in Web Usage Mining", Proc. of Seventh International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA 2012), Advances in Intelligent Systems and Computing Vol. 202, Springer India, 407-416.
  9. Zhang Huiying 2004, "An Intelligent Algorithm of Data Pre-processing in Web Usage Mining", Proceedings of the 5th World Congress an Intelligent Control and Automation, Vol. 4, IEEE, 3119 – 3123.
  10. NASA Kennedy space Centre http://ita. ee. lbl. gov/html/contrib/NASA-HTTP. html
  11. R. Suresh and R. Padmajavalli, 2007, "An Overview of Data Preprocessing in Data and Web Usage Mining", First International Conference on Digital Information Management, 193-198.
  12. G. Arumugam and S. Suguna, 2008, "Predictive Prefetching Framework Based on New Pre-processing Algorithms towards Latency Reduction", Asian Journal of Information Technology, Vol. 7, No. 3, 87-99.
  13. Das, R. and Turkoglu, I. , 2009, "Creating meaningful data from web logs for improving the impressiveness of a website by using path analysis method", Expert Systems with Applications, Vol. 36, Science Direct, 6635–6644.
  14. Liu, B. , 2007, Web data mining: Exploring hyperlinks, contents and usage data, Springer, ISBN: 13-978-3-540-37881-5 (532p. ).
Index Terms

Computer Science
Information Sciences

Keywords

Web Usage Data Web Log Pre-processing.

Powered by PhDFocusTM