Web user session clustering using modified K-means algorithm

G. Poornalatha, Prakash S. Raghavendra

Research output: Chapter in Book/Report/Conference proceedingConference contribution

17 Citations (SciVal)


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 e-commerce 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.

Original languageEnglish
Title of host publicationAdvances in Computing and Communications - First International Conference, ACC 2011, Proceedings
Number of pages10
Volume191 CCIS
EditionPART 2
Publication statusPublished - 2011
Event1st International Conference on Advances in Computing and Communications, ACC 2011 - Kochi, India
Duration: 22-07-201124-07-2011

Publication series

NameCommunications in Computer and Information Science
NumberPART 2
Volume191 CCIS
ISSN (Print)1865-0929


Conference1st International Conference on Advances in Computing and Communications, ACC 2011

All Science Journal Classification (ASJC) codes

  • Computer Science(all)


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