A New Clustering Approach based on Page's Path Similarity for Navigation Patterns Mining
Abstract
In recent years, predicting the user's next request in web navigation has received much attention. An information source to be used for dealing with such problem is the left information by the previous web users stored at the web access log on the web servers. Purposed systems for this problem work based on this idea that if a large number of web users request specific pages of a website on a given session, it can be concluded that these pages are satisfying similar information needs, and therefore they are conceptually related. In this study, a new clustering approach is introduced that employs logical path storing of a website pages as another parameter which is regarded as a similarity parameter and conceptual relation between web pages. The results of simulation have shown that the proposed approach is more than others precise in determining the clusters.
Keywords
Cite
@article{arxiv.1003.1450,
title = {A New Clustering Approach based on Page's Path Similarity for Navigation Patterns Mining},
author = {Heidar Mamosian and Amir Masoud Rahmani and Mashalla Abbasi Dezfouli},
journal= {arXiv preprint arXiv:1003.1450},
year = {2010}
}
Comments
Pages IEEE format, International Journal of Computer Science and Information Security, IJCSIS February 2010, ISSN 1947 5500, http://sites.google.com/site/ijcsis/