System Notification:
We are currently experiencing intermittent issues impacting performance. We apologize for the inconvenience.
By Topic

An efficient minimum spanning tree based clustering algorithm

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Jana, P.K. ; Dept. of Comput. Sci. & Eng., Indian Sch. of Mines, Dhanbad, India ; Naik, A.

Clustering analysis has been an emerging research issue in data mining due its variety of applications. In the recent years, it has become an essential tool for gene expression analysis. Many clustering algorithms have been proposed so far. However, each algorithm has its own merits and demerits and can not work for all real situations. In this paper, we present a clustering algorithm that is inspired by minimum spanning tree. To automate and evaluate our algorithm, we incorporate the concept of ratio between the intra-cluster distance (measuring compactness) and the inter-cluster distance (measuring isolation). Experimental results on some complex as well as real world data sets reveal that the proposed algorithm is efficient and competitive with the existing clustering algorithms.

Published in:

Methods and Models in Computer Science, 2009. ICM2CS 2009. Proceeding of International Conference on

Date of Conference:

14-15 Dec. 2009