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Data Clustering: A Review (1999)

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by A K Jain , M N Murty , P. J. Flynn
Venue:ACM COMPUTING SURVEYS
Citations:912 - 9 self
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User correction supplied by amr537

DatumValueSource
TITLE Data Clustering: A Review user correction - Legacy Corrections
AUTHOR NAME A K Jain user correction
AUTHOR AFFIL Michigan State University, East Lansing. user correction
AUTHOR NAME M N Murty user correction
AUTHOR AFFIL Indian Institute of Science, Bangalore, India. user correction
AUTHOR NAME P. J. Flynn user correction
AUTHOR AFFIL The Ohio State University, Columbus. 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 reflects 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 - Legacy Corrections
VENUE ACM COMPUTING SURVEYS user correction
VENUE TYPE article user correction
PAGES 264--323 user correction
VOLUME 31 user correction
NUMBER 3 user correction
CITATIONS 223 found ParsCit 1.0
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