Thursday 28th of March 2024
 

A Propound Method for the Improvement of Cluster Quality


Shveta Kundra Bhatia and V. S. Dixit

In this paper Knockout Refinement Algorithm (KRA) is proposed to refine original clusters obtained by applying SOM and K-Means clustering algorithms. KRA Algorithm is based on Contingency Table concepts. Metrics are computed for the Original and Refined Clusters. Quality of Original and Refined Clusters are compared in terms of metrics. The proposed algorithm (KRA) is tested in the educational domain and results show that it generates better quality clusters in terms of improved metric values.

Keywords: Web Usage Mining, K-Means, Self Organizing Maps, Knockout Refinement Algorithm (KRA), Davies Bouldin (DB) Index, Dunns Index, Precision, Recall, F-Measure

Download Full-Text


ABOUT THE AUTHORS

Shveta Kundra Bhatia
Shveta Kundra Bhatia is working as an Assistant Professor in the Department Of Computer Science, Swami Sharaddhanand College, University of Delhi. Her research area is Web Usage Mining and is currently pursuing PhD under Dr. V.S. Dixit from Department of Computer Science, University of Delhi.

V. S. Dixit
Dr. V. S. Dixit is working in the Department Of Computer Science, Atma Ram Sanatan Dharam College, University of Delhi. His research area is Queuing theory, Peer to Peer systems, Web Usage Mining and Web Recommender Systems. He is currently engaged in doing the research. He is Life member of IETE.


IJCSI Published Papers Indexed By:

 

 

 

 
+++
About IJCSI

IJCSI is a refereed open access international journal for scientific papers dealing in all areas of computer science research...

Learn more »
Join Us
FAQs

Read the most frequently asked questions about IJCSI.

Frequently Asked Questions (FAQs) »
Get in touch

Phone: +230 911 5482
Email: info@ijcsi.org

More contact details »