Efficient and Effective Clustering Methods for Spatial Data Mining

Efficient and Effective Clustering Methods for Spatial Data Mining (1994)

by Raymond T. Ng , Jiawei Han

Citations:

User correction supplied by SystemCorrections

Datum	Value	Source
TITLE	Efficient and Effective Clustering Methods for Spatial Data Mining	INFERENCE
AUTHOR NAME	Raymond T. Ng	user correction - Legacy Corrections
AUTHOR AFFIL	Department of Computer Science; University of British Columbia	user correction - Legacy Corrections
AUTHOR ADDR	Vancouver, B.C., V6T 1Z4, Canada	user correction - Legacy Corrections
AUTHOR NAME	Jiawei Han	user correction - Legacy Corrections
AUTHOR AFFIL	School of Computing Sciences; Simon Fraser University	user correction - Legacy Corrections
AUTHOR ADDR	Burnaby, B.C., V5A 1S6, Canada	user correction - Legacy Corrections
ABSTRACT	Spatial data mining is the discovery of interesting relationships and characteristics that may exist implicitly in spatial databases. In this paper, we explore whether clustering methods have a role to play in spatial data mining. To this end, we develop a new clustering method called CLARANS which is based on randomized search. We also de- velop two spatial data mining algorithms that use CLARANS. Our analysis and experiments show that with the assistance of CLARANS, these two algorithms are very effective and can lead to discoveries that are difficult to find with current spatial data mining algorithms.	user correction - Legacy Corrections
YEAR	1994	INFERENCE
VENUE TYPE	CONFERENCE	INFERENCE
PAGES	144--155	INFERENCE
CITATIONS	13 found	ParsCit 1.0