Article

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

Authors:

Gholamhosein Sheikholeslami,

Surojit Chatterjee,

Aidong ZhangAuthors Info & Claims

VLDB '98: Proceedings of the 24rd International Conference on Very Large Data Bases

Pages 428 - 439

Published: 24 August 1998 Publication History

Abstract

No abstract available.

References

[1]

{AF97} D. Allard and C. Fraley. Non parametric maximum likelihood estimation of features in spatial process using voronoi tesselation. Journal of the American Statistical Association , December 1997.

Google Scholar

[2]

{BR95} S. Byers and A. E. Raftery. Nearest neighbor clutter removal for estimating features in spatial point processes. Technical Report 295, Department of Statistics, University of Washington, 1995.

Google Scholar

[3]

{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.

Google Scholar

[4]

{HJS94} M. L. Hilton, Björn D. Jawerth, A. Sengupta: Compressing Still and Moving Images with Wavelets. Multimedia Syst. 2(5): 218-227(1994).

Digital Library

Google Scholar

[5]

{Hor88} Berthold Klaus Paul Horn. Robot Vision. The MIT Press, forth edition, 1988.

Google Scholar

[6]

{KR90} L. Kaufman and P. J. Rousseeuw. Finding Groups in Data: an Introduction to Cluster Analysis. John Wiley & Sons, 1990.

Google Scholar

[7]

{Mal89a} S. Mallat. Multiresolution approximation and wavelet orthonormal bases of L²(R). Transactions of American Mathematical Society, 315:69-87, September 1989.

Google Scholar

[8]

{Mal89b} S. Mallat. A theory for multiresolution signal decomposition: the wavelet representation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 11:674-693, July 1989.

Digital Library

Google Scholar

[9]

{NH94} Raymond T. Ng, Jiawei Han: Efficient and Effective Clustering Methods for Spatial Data Mining. VLDB 1994: 144- 155.

Digital Library

Google Scholar

[10]

{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).

Digital Library

Google Scholar

[11]

{PFG97} E.J. Pauwels, P. Fiddelaers, and L. Van Gool. DOG-based unsupervized clustering for CBIR. In Proceedings of the 2nd International Conference on Visual Information Systems, pages 13-20, 1997.

Google Scholar

[12]

{SC94} J. R. Smith and S. Chang. Transform Features For Texture Classification and Discrimination in Large Image Databases. In Proceedings of the IEEE International Conference on Image Processing, pages 407- 411, 1994.

Crossref

Google Scholar

[13]

{Sch92} Robert Schalkoff. Pattern Recognition: Statistical, Structural and Neural Approaches . John Wiley & Sons, Inc., 1992.

Google Scholar

[14]

{SN96} Gilbert Strang and Truong Nguyen. Wavelets and Filter Banks. Wellesley-Cambridge Press, 1996.

Google Scholar

[15]

{SV82} Yossi Shiloach, Uzi Vishkin: An O(log n) Parallel Connectivity Algorithm. J. Algorithms 3(1): 57-67(1982).

Crossref

Google Scholar

[16]

{SZ97} G. Sheikholeslami and A. Zhang. An Approach to Clustering Large Visual Databases Using Wavelet Transform. In Proceedings of the SPIE Conference on Visual Data Exploration and Analysis IV, San Jose, February 1997.

Crossref

Google Scholar

[17]

{SZB97} G. Sheikholeslami, A. Zhang, and L. Bian. Geographical Data Classification and Retrieval. In Proceedings of the 5th ACM International Workshop on Geographic Information Systems, pages 58-61, 1997.

Digital Library

Google Scholar

[18]

{URB97} Greet Uytterhoeven, Dirk Roose, and Adhemar Bultheel. Wavelet transforms using lifting scheme. Technical Report ITA-Wavelets Report WP 1.1, Katholieke Universiteit Leuven, Department of Computer Science, Belgium, April 1997.

Google Scholar

[19]

{Vai93} P. P. Vaidyanathan. Multirate Systems And Filter Banks. Prentice Hall Signal Processing Series. Prentice Hall, Englewood Cliffs, NJ, 1993.

Digital Library

Google Scholar

[20]

{WYM97} Wei Wang, Jiong Yang, Richard R. Muntz: STING: A Statistical Information Grid Approach to Spatial Data Mining. VLDB 1997: 186-195.

Digital Library

Google Scholar

[21]

{ZRL96} Tian Zhang, Raghu Ramakrishnan, Miron Livny: BIRCH: An Efficient Data Clustering Method for Very Large Databases. SIGMOD Conference 1996: 103-114.

Digital Library

Google Scholar

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Published In

VLDB '98: Proceedings of the 24rd International Conference on Very Large Data Bases

August 1998

695 pages

ISBN:1558605665

Publisher

Morgan Kaufmann Publishers Inc.

San Francisco, CA, United States

Publication History

Published: 24 August 1998

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VLDB98

VLDB98: International Conference on Very Large Databases

August 24 - 27, 1998

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Nikolakaki SMavroforakis CEne ATerzi EChampin PGandon FMédini LLalmas MIpeirotis P(2018)Mining Tours and Paths in Activity NetworksProceedings of the 2018 World Wide Web Conference10.1145/3178876.3186112(459-468)Online publication date: 10-Apr-2018
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Pandove DGoel SRani R(2018)Systematic Review of Clustering High-Dimensional and Large DatasetsACM Transactions on Knowledge Discovery from Data10.1145/313208812:2(1-68)Online publication date: 23-Jan-2018
https://dl.acm.org/doi/10.1145/3132088
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Chen LYu TChirkova RBailey JMoffat AAggarwal Cde Rijke MKumar RMurdock VSellis TYu J(2015)WaveCluster with Differential PrivacyProceedings of the 24th ACM International on Conference on Information and Knowledge Management10.1145/2806416.2806546(1011-1020)Online publication date: 17-Oct-2015
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Recommendations

Parallel WaveCluster: A linear scaling parallel clustering algorithm implementation with application to very large datasets

WaveCluster with Differential Privacy

An improved WaveCluster algorithm based on ICA

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