Access Patterns in Web Log Data: A Review

Authors

  • Mohammed Hamed Ahmed Elhiber Sudan University of Science and Technology, Faculty of Computer Science
  • Ajith Abraham Machine Intelligence Research Labs (MIR Labs), Scientific Network for Innovation and Research Excellence

Keywords:

World Wide Web, data mining, Web Usage Mining, OLAP

Abstract

The traffic on World Wide Web is increasing rapidly and huge amount of information is generated due to users interactions with web sites. To utilize this information, identifying usage pattern of users is very important. Web Usage Mining is the application of data
mining techniques to discover the useful, hidden information about the users and interesting patterns from data extracted from Web Log files. It supports to know frequently accessed pages, predict user navigation, improve web site structure etc. In order to apply Web
Usage Mining, various steps are performed. This paper discusses the process of Web Usage Mining consisting steps: Data Collection, Pre-processing, Pattern Discovery and Pattern Analysis. It has also presented several approaches such as statistical analysis; clustering,
association rules and sequential pattern are being used to discover patterns in web usage mining. The pattern analysis phase means applying data mining techniques such as SQL and OLAP on the pattern discovery data to filter insignificant information to obtain the valuable information.

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Published

2013-10-01

How to Cite

Mohammed Hamed Ahmed Elhiber, & Ajith Abraham. (2013). Access Patterns in Web Log Data: A Review . Journal of Network and Innovative Computing, 1, 8. Retrieved from https://cspub-jnic.org/index.php/jnic/article/view/44

Issue

Vol. 1 (2013)

Section

Review

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