On Data Clustering Analysis: Scalability, Constraints and Validation
- Osmar R. Zaiane, University of Alberta (Database)
- Andrew Foss, University of Alberta
- Chi-Hoon Lee, Dept of Computing Science
- Weinan Wang
Clustering is the problem of grouping data based on similarity. While this problem has attracted the attention of many researchers for many years, we are witnessing a resurgence of interest in new clustering techniques. In this paper we discuss some very recent clustering approaches and recount our experience with some of these algorithms. We also present the problem of clustering in the presence of constraints and discuss the issue of clustering validation.
Citation
O. Zaiane, A. Foss, C. Lee, W. Wang. "On Data Clustering Analysis: Scalability, Constraints and Validation". Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), Taipei, Taiwan, pp 28-39, May 2002.| Keywords: | |
| Category: | In Conference |
| Web Links: | ACM Digital Library |
BibTeX
@incollection{Zaiane+al:PAKDD02,
author = {Osmar R. Zaiane and Andrew Foss and Chi-Hoon Lee and Weinan Wang},
title = {On Data Clustering Analysis: Scalability, Constraints and
Validation},
Pages = {28-39},
booktitle = {Pacific-Asia Conference on Knowledge Discovery and Data Mining
(PAKDD)},
year = 2002,
}Last Updated: February 03, 2020Submitted by Sabina P
