Using the fractal dimension to cluster datasets

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Using the fractal dimension to cluster datasets

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International Conference on Knowledge Discovery and Data Mining archive
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining table of contents

Boston, Massachusetts, United States

Pages: 260 - 264

Year of Publication: 2000

ISBN:1-58113-233-6

Authors

Daniel Barbará	George Mason University, ISE Dept., MSN 4A4, Fairfax, VA
Ping Chen	George Mason University, ISE Dept., MSN 4A4, Fairfax, VA

Sponsors

SIGKDD: ACM Special Interest Group on Knowledge Discovery in Data
AAAI : Am Assoc for Artifical Intelligence
SIGART: ACM Special Interest Group on Artificial Intelligence
SIGMOD: ACM Special Interest Group on Management of Data

Publisher

ACM New York, NY, USA

Bibliometrics

Downloads (6 Weeks): 10, Downloads (12 Months): 78, Citation Count: 10

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REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

	1	E. Backer, Computer-assisted reasoning in cluster analysis, Prentice Hall International (UK) Ltd., Hertfordshire, UK, 1995
	2	D. Barbara and P. Chen. Using the Fractal Dimension to Cluster Datasets. Technical Report ISE-TR-99-08, George Mason University, Information and Software Engineering Department, Oct. 1999.
	3	P. Grassberger. Generalized Dimensions of Strange Attractors. Physics Letters, 97A:227-230, 1983.
	4	P. Grassberger and I. Procaccia. Characterization of Strange Attractors. Physical Review Letters, 50(5):346-349, 1983.
	5	Anil K. Jain , Richard C. Dubes, Algorithms for clustering data, Prentice-Hall, Inc., Upper Saddle River, NJ, 1988
	6	L. Liebovitch and T. Toth. A Fast Algorithm to Determine Fractal Dimensions by Box Countig. Physics Letters, 141A(8), 1989.
	7	B. Mandelbrot. The Fractal Geometry of Nature. W.H. Freeman, New York, 1983.
	8	J. Sarraille and P. DiFalco. FD3. http://tori.postech.ac.kr/softwares/.
	9	E. Schikuta. Grid clustering: An efficient hierarchical method for very large data sets. In Proceedings of the 13th Conference on Pattern Recognition, IEEE Computer Society Press, pages 101-105, 1996.
	10	M. Schroeder. Fractals, Chaos, Power Laws: Minutes from an Infinite Paradise. W.H. Freeman, New York, 1991.
	11	Gholamhosein Sheikholeslami , Surojit Chatterjee , Aidong Zhang, WaveCluster: A Multi-Resolution Clustering Approach for Very Large Spatial Databases, Proceedings of the 24rd International Conference on Very Large Data Bases, p.428-439, August 24-27, 1998
	12	Wei Wang , Jiong Yang , Richard R. Muntz, STING: A Statistical Information Grid Approach to Spatial Data Mining, Proceedings of the 23rd International Conference on Very Large Data Bases, p.186-195, August 25-29, 1997

CITED BY 10

	Agma Traina , Caetano Traina , Spiros Papadimitriou , Christos Faloutsos, Tri-plots: scalable tools for multidimensional data mining, Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining, p.184-193, August 26-29, 2001, San Francisco, California
	Daniel Barbará, Requirements for clustering data streams, ACM SIGKDD Explorations Newsletter, v.3 n.2, January 2002
	Daniel Barbará , Yi Li , Julia Couto, COOLCAT: an entropy-based algorithm for categorical clustering, Proceedings of the eleventh international conference on Information and knowledge management, November 04-09, 2002, McLean, Virginia, USA
	Christian Böhm , Karin Kailing , Peer Kröger , Arthur Zimek, Computing Clusters of Correlation Connected objects, Proceedings of the 2004 ACM SIGMOD international conference on Management of data, June 13-18, 2004, Paris, France
	Huanmei Wu , Betty Salzberg , Donghui Zhang, Online event-driven subsequence matching over financial data streams, Proceedings of the 2004 ACM SIGMOD international conference on Management of data, June 13-18, 2004, Paris, France
	Aristides Gionis , Alexander Hinneburg , Spiros Papadimitriou , Panayiotis Tsaparas, Dimension induced clustering, Proceeding of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining, August 21-24, 2005, Chicago, Illinois, USA
	Gloria Haro , Gregory Randall , Guillermo Sapiro, Translated Poisson Mixture Model for Stratification Learning, International Journal of Computer Vision, v.80 n.3, p.358-374, December 2008
	Xiang Zhang , Feng Pan , Wei Wang, REDUS: finding reducible subspaces in high dimensional data, Proceeding of the 17th ACM conference on Information and knowledge management, October 26-30, 2008, Napa Valley, California, USA
	Guang-Hui Yan , Li-Song Liu , Lin-Na Du , Xia-Xia Yang , Zhi-Cheng Ma , Xiao-Min Zhang, Multifractal-based cluster hierarchy optimisation algorithm, International Journal of Business Intelligence and Data Mining, v.3 n.4, p.353-374, January 2009
	Hans-Peter Kriegel , Peer Kröger , Arthur Zimek, Clustering high-dimensional data: A survey on subspace clustering, pattern-based clustering, and correlation clustering, ACM Transactions on Knowledge Discovery from Data (TKDD), v.3 n.1, p.1-58, March 2009