Research and application of clustering algorithm for arbitrary data set

Files in This Item:
File Description SizeFormat 
CCSSE.pdf446.6 kBAdobe PDFDownload
Title: Research and application of clustering algorithm for arbitrary data set
Authors: Song, Yu-Chen
O'Grady, Michael J.
O'Hare, G. M. P. (Greg M. P.)
Permanent link:
Date: Dec-2008
Online since: 2009-08-10T15:57:35Z
Abstract: This paper discusses the theory and algorithmic design of the CADD (clustering algorithm based on object density and direction) algorithm. This algorithm seeks to harness the respective advantages of the k-means and DENCLUE algorithms. Clustering results are illustrated using both a simple data set and one from the geological domain. Results indicate that CADD is robust in that automatically determines the number K of clusters, and is capable of identifying clusters of multiple shapes and sizes.
Funding Details: Science Foundation Ireland
Type of material: Conference Publication
Publisher: IEEE Computer Society
Copyright (published version): 2008 by The Institute of Electrical and Electronics Engineers, Inc
Subject LCSH: Cluster analysis--Computer programs
DOI: 10.1109/CSSE.2008.415
Other versions:
Language: en
Status of Item: Peer reviewed
Is part of: Proceedings : International Conference on Computer Science and Software Engineering : CSSE 2008 : Volume 04
Conference Details: Paper presented at the 2008 International Conference on Computer Science and Software Engineering, December 12-14, 2008, Wuhan, China
ISBN: 978-0-7695-3336-0
Appears in Collections:CLARITY Research Collection
Computer Science Research Collection

Show full item record

Citations 50

Last Week
Last month
checked on Feb 11, 2019

Page view(s) 20

checked on May 25, 2018

Download(s) 5

checked on May 25, 2018

Google ScholarTM



This item is available under the Attribution-NonCommercial-NoDerivs 3.0 Ireland. No item may be reproduced for commercial purposes. For other possible restrictions on use please refer to the publisher's URL where this is made available, or to notes contained in the item itself. Other terms may apply.