Web User Session Clustering Using Modified K-Means Algorithm

Poornalatha, G and Prakash, Raghavendra S (2011) Web User Session Clustering Using Modified K-Means Algorithm. Advances in Computing and Communications, 191. pp. 243-252.

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The proliferation of internet along with the attractiveness of the web in recent years has made web mining as the research area of great magnitude. Web mining essentially has many advantages which makes this technology attractive to researchers. The analysis of web user’s navigational pattern within a web site can provide useful information for applications like, server performance enhancements, restructuring a web site, direct marketing in ecommerce etc. The navigation paths may be explored based on some similarity criteria, in order to get the useful inference about the usage of web. The objective of this paper is to propose an effective clustering technique to group users’ sessions by modifying K-means algorithm and suggest a method to compute the distance between sessions based on similarity of their web access path, which takes care of the issue of the user sessions that are of variable length.

Item Type: Article
Uncontrolled Keywords: web mining clustering K-means Jaccard Index
Subjects: Engineering > MIT Manipal > Information and Communication Technology
Depositing User: MIT Library
Date Deposited: 07 Jan 2016 14:47
Last Modified: 27 Jul 2016 11:10
URI: http://eprints.manipal.edu/id/eprint/145018

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