IJERT-EMS
IJERT-EMS

An Enhanced Clustering Technique for Web Usage Mining


An Enhanced Clustering Technique for Web Usage Mining
Authors : V.CHITRAA, Dr.ANTONY SELVADOSS THANAMANI
Publication Date: 30-06-2012

Authors

Author(s):  V.CHITRAA, Dr.ANTONY SELVADOSS THANAMANI

Published in:   International Journal of Engineering Research & Technology

License:  This work is licensed under a Creative Commons Attribution 4.0 International License.

Website: www.ijert.org

Volume/Issue:   Vol.1 - Issue 4 (June- 2012)

e-ISSN:   2278-0181

Abstract

The World Wide Web has become the default knowledge resource for many years of endeavor, and organizations need to understand their customers behavior, preferences and future needs. Web personalization is an active research topic in which user session clustering is done to understand users activities. Cluster analysis is a widely used data mining algorithmand is a process of partitioning a set of data objects into a number of object clusters, where each data object shares the high similarity with the other objects within the same cluster but is quite dissimilar to objects in other clusters. In this paper an enhanced method to partition into accurate clusters is discussed. The algorithm is carried out in two steps and clusters are with high quality. The experimental results show the performance of the proposed algorithm and comparatively it gives the good results.

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