Interactive exploration of very large relational datasets through 3D dynamic projections

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Interactive exploration of very large relational datasets through 3D dynamic projections

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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: 236 - 243

Year of Publication: 2000

ISBN:1-58113-233-6

Author

Li Yang

Department of Computer Science, Western Michigan University, Kalamazoo, Michigan

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): 8, Downloads (12 Months): 52, 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.

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CITED BY 10

	Li Yang, Visual Exploration of Large Relational Data Sets through 3D Projections and Footprint Splatting, IEEE Transactions on Knowledge and Data Engineering, v.15 n.6, p.1460-1471, November 2003
	Michael Berthold , David J. Hand, References, Intelligent data analysis, Springer-Verlag New York, Inc., New York, NY, 2003
	Keke Chen , Ling Liu, Cluster rendering of skewed datasets via visualization, Proceedings of the 2003 ACM symposium on Applied computing, March 09-12, 2003, Melbourne, Florida
	Li Yang, Distance-preserving mapping of patterns to 3-space, Pattern Recognition Letters, v.25 n.1, p.119-128, 5 January 2004
	Keke Chen , Ling Liu, ClusterMap: labeling clusters in large datasets via visualization, Proceedings of the thirteenth ACM international conference on Information and knowledge management, November 08-13, 2004, Washington, D.C., USA
	Keke Chen , Ling Liu, VISTA: validating and refining clusters via visualization, Information Visualization, v.3 n.4, p.257-270, December 2004
	Charu C. Aggarwal, A Human-Computer Interactive Method for Projected Clustering, IEEE Transactions on Knowledge and Data Engineering, v.16 n.4, p.448-460, April 2004
	Enrico Bertini , Giuseppe Santucci, Give chance a chance: modeling density to enhance scatter plot quality through random data sampling, Information Visualization, v.5 n.2, p.95-110, June 2006
	Keke Chen , Ling Liu, iVIBRATE: Interactive visualization-based framework for clustering large datasets, ACM Transactions on Information Systems (TOIS), v.24 n.2, p.245-294, April 2006
	Charu C. Aggarwal, On the use of Human-Computer Interaction for Projected Nearest Neighbor Search, Data Mining and Knowledge Discovery, v.13 n.1, p.89-117, July 2006