Data Clustering: A Review

Data Clustering: A Review (1999)

by A. K. Jain , M. N. Murty , P. J. Flynn

Citations:

912 - 9 self

User correction supplied by mph

Datum	Value	Source
TITLE	Data Clustering: A Review	user correction
AUTHOR NAME	A. K. Jain	user correction
AUTHOR AFFIL	Michigan State University	user correction
AUTHOR NAME	M. N. Murty	user correction
AUTHOR AFFIL	Indian Institute of Science	user correction
AUTHOR NAME	P. J. Flynn	user correction
AUTHOR AFFIL	The Ohio State University	user correction
ABSTRACT	Clustering is the unsupervised classification of patterns (observations, data items, or feature vectors) into groups (clusters). The clustering problem has been addressed in many contexts and by researchers in many disciplines; this re ects its broad appeal and usefulness as one of the steps in exploratory data analysis. However, clustering is a difficult problem combinatorially and differences in assumptions and contexts in different communities has made the transfer of useful generic concepts and methodologies slow to occur. This paper presents an overview of pattern clustering methods from a statistical pattern recognition perspective, with a goal of providing useful advice and references to fundamental concepts accessible to the broad community of clustering practitioners. We present a taxonomy of clustering techniques and identify cross-cutting themes and recent advances. We also describe some important applications of clustering algorithms such as image segmentation, object recognition, and information retrieval.	user correction
YEAR	1999	user correction
CITATIONS	203 found	ParsCit 1.0