Anzeige
Erschienen in:
2011 | OriginalPaper | Buchkapitel
Web User Session Clustering Using Modified K-Means Algorithm
verfasst von : G. Poornalatha, Prakash S. Raghavendra
Erschienen in: Advances in Computing and Communications
Verlag: Springer Berlin Heidelberg
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
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.