WaveCluster: A Multi-Resolution Clustering Approach for Very Large Spatial Databases.

Gholamhosein Sheikholeslami, Surojit Chatterjee, Aidong Zhang: WaveCluster: A Multi-Resolution Clustering Approach for Very Large Spatial Databases. VLDB 1998: 428-439

@inproceedings{DBLP:conf/vldb/SheikholeslamiCZ98,
  author    = {Gholamhosein Sheikholeslami and
               Surojit Chatterjee and
               Aidong Zhang},
  editor    = {Ashish Gupta and
               Oded Shmueli and
               Jennifer Widom},
  title     = {WaveCluster: A Multi-Resolution Clustering Approach for Very
               Large Spatial Databases},
  booktitle = {VLDB'98, Proceedings of 24rd International Conference on Very
               Large Data Bases, August 24-27, 1998, New York City, New York,
               USA},
  publisher = {Morgan Kaufmann},
  year      = {1998},
  isbn      = {1-55860-566-5},
  pages     = {428-439},
  ee        = {db/conf/vldb/SheikholeslamiCZ98.html},
  crossref  = {DBLP:conf/vldb/98},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}

Abstract

Many applications require the management of spatial data. Clustering large spatial databases is an important problem which tries to find the densely populated regions in the feature space to be used in datamining, knowledge discovery, or efficient information retrieval. A good clustering approach should be efficient and detect clusters of arbitrary shape. It must be insensitive to the outliers (noise) and the order of input data. We propose WaveCluster, a novel clustering approach based on wavelet transforms, which satisfies all the above requirements. Using multi- resolution property of wavelet transforms, we can effectivelyidentify arbitrary shape clusters at different degrees of accuracy. We also demonstrate that WaveCluster is highly efficient in terms of time complexity. Experimental results on very large data sets are presented which show the efficiency and effectiveness of the proposed approach compared to the other recent clustering methods.

Copyright © 1998 by the VLDB Endowment. Permission to copy without fee all or part of this material is granted provided that the copies are not made or distributed for direct commercial advantage, the VLDB copyright notice and the title of the publication and its date appear, and notice is given that copying is by the permission of the Very Large Data Base Endowment. To copy otherwise, or to republish, requires a fee and/or special permission from the Endowment.

Online Paper

Download PDF file (www.vldb.org, Darmstadt, Germany)
Download PDF file (www.acm.org, New York, USA)

ACM SIGMOD DiSC

CDROM Version: Load the CDROM "DiSC, Volume 1 Number 1" and ...

Windows: Click the letter of your CD drive
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z
Mac: Click here
UNIX/LINUX: mount the CD and click on the path of your mount point:
/Anthology/Disc99_1 or /cdrom

ACM SIGMOD Anthology

DVD Version: Load ACM SIGMOD Anthology DVD 1" and ...

Windows: Click the letter of your CD drive
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z
Mac: Click here
UNIX/LINUX: mount the DVD and click on the path of your mount point:
/Anthology/aDVD1 or /dvd

Printed Edition

Ashish Gupta, Oded Shmueli, Jennifer Widom (Eds.): VLDB'98, Proceedings of 24rd International Conference on Very Large Data Bases, August 24-27, 1998, New York City, New York, USA. Morgan Kaufmann 1998, ISBN 1-55860-566-5
Contents

References

[AF97]: ...
[BR95]: ...
[EKSX96]: Martin Ester, Hans-Peter Kriegel, Jörg Sander, Xiaowei Xu: A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise. KDD 1996: 226-231
[HJS94]: M. L. Hilton, Björn D. Jawerth, A. Sengupta: Compressing Still and Moving Images with Wavelets. Multimedia Syst. 2(5): 218-227(1994)
[Hor88]: ...
[KR90]: ...
[Mal89a]: ...
[Mal89b]: ...
[NH94]: Raymond T. Ng, Jiawei Han: Efficient and Effective Clustering Methods for Spatial Data Mining. VLDB 1994: 144-155
[NS80]: David Nassimi, Sartaj Sahni: Finding Connected Components and Connected Ones on a Mesh-Connected Parallel Computer. SIAM J. Comput. 9(4): 744-757(1980)
[PFG97]: ...
[SC94]: ...
[Sch92]: ...
[SN96]: ...
[SV82]: Yossi Shiloach, Uzi Vishkin: An O(log n) Parallel Connectivity Algorithm. J. Algorithms 3(1): 57-67(1982)
[SZ97]: ...
[SZB97]: ...
[URB97]: ...
[Vai93]: ...
[WYM97]: Wei Wang, Jiong Yang, Richard R. Muntz: STING: A Statistical Information Grid Approach to Spatial Data Mining. VLDB 1997: 186-195
[ZRL96]: Tian Zhang, Raghu Ramakrishnan, Miron Livny: BIRCH: An Efficient Data Clustering Method for Very Large Databases. SIGMOD Conference 1996: 103-114