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Papyrus: a system for data mining over local and wide area clusters and super-clusters

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Conference on High Performance Networking and Computing archive
Proceedings of the 1999 ACM/IEEE conference on Supercomputing (CDROM) table of contents

Portland, Oregon, United States

Article No. 63

Year of Publication: 1999

ISBN:1-58113-091-0

Authors

S. Bailey	National Center for Data Mining, University of Illinois at Chicago
R. Grossman	National Center for Data Mining, University of Illinois at Chicago and Magnify, Inc.
H. Sivakumar	National Center for Data Mining, University of Illinois at Chicago
A. Turinsky	National Center for Data Mining, University of Illinois at Chicago

Sponsors

IEEE-CS\TCCA : TC on Computer Arhitecture
SIGARCH: ACM Special Interest Group on Computer Architecture

Publisher

ACM New York, NY, USA

Bibliometrics

Downloads (6 Weeks): 2, Downloads (12 Months): 20, Citation Count: 12

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references cited by index terms collaborative colleagues

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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	P. Chan and H. Kargupta, editors, Proceedings of the Workshop on Distributed Data Mining, The Fourth International Conference on Knowledge Discovery and Data Mining New York City, 1999, to appear.
	2	T. G. Dietterich, Machine Learning Research: Four Current Directions, AI Magazine Volume 18, pages 97-136, 1997.
	3	DataSpace, Protocols and Languages for Distributed Data Mining, http://www.ncdm.uic.edu.
	4	R. L. Grossman, H. Bodek, D. Northcutt, and H. V. Poor, "Data Mining and Tree-based Optimization," Proceedings of the Second International Conference on Knowledge Discovery and Data Mining, E. Simoudis, J. Han and U. Fayyad, editors, AAAI Press, Menlo Park, California, 1996, pp 323-326.
	5	The Terabyte Challenge: An Open, Distributed Testbed for Managing and Mining Massive Data Sets, Proceedings of the 1998 Conference on Supercomputing, IEEE.
	6	Robert Grossman, Stuart Bailey, Simon Kasif, Don Mon, Ashok Ramu and Balinder Malhi, The Preliminary Design of Papyrus: A System for High Performance, Distributed Data Mining over Clusters, Meta-Clusters and Super-Clusters, Proceedings of the Workshop on Distributed Data Mining, The Fourth International Conference on Knowledge Discovery and Data Mining New York City, P. Chan and H. Kargupta, editors, to appear.
	7	R. L. Grossman, An Overview of High Performance and Distributed Data Mining Systems, submitted for publication.
	8	R. L. Grossman, S. Bailey, A. Ramu, B. Malhi, P. Hallstrom, I. Pulleyn, and X. Qin, The Management and Mining of Multiple Predictive Models Using the Predictive Modeling Markup Language (PMML), Information and System Technology, Volume 41, pages 589-595, 1999.
	9	Y. Guo, S. M. Rueger, J. Sutiwaraphun, J.; and J. Forbes-Millott, Meta-Learnig for Parallel Data Mining, in Proceedings of the Seventh Parallel Computing Workshop, pages 1-2, 1997.
	10	H. Kargupta, I. Hamzaoglu and B. Stafford, Scalable, Distributed Data Mining Using an Agent Based Architecture, in D. Heckerman, H. Mannila, D. Pregibon, and R. Uthurusamy, editors, Proceedings the Third International Conference on the Knowledge Discovery and Data Mining, AAAI Press, Menlo Park, California, pages 211-214, 1997.
	11	Danny B. Lange , Oshima Mitsuru, Programming and Deploying Java Mobile Agents Aglets, Addison-Wesley Longman Publishing Co., Inc., Boston, MA, 1998
	12	Reagan Moore , Thomas A. Prince , Mark Ellisman, Data-intensive computing and digital libraries, Communications of the ACM, v.41 n.11, p.56-62, Nov. 1998 [doi>10.1145/287831.287840]
	13	See http://www.dmg.org.
	14	J. Ross Quinlan, C4.5: programs for machine learning, Morgan Kaufmann Publishers Inc., San Francisco, CA, 1993
	15	A. E. Raftery, D. Madigan, and J. A. Hoeting, 1996. Bayesian Model Averaging for Linear Regression Models, Journal of the American Statistical Association, Volume92, pages 179-191, 1996.
	16	S. Stolfo, A. L. Prodromidis, and P. K. Chan, JAM: Java Agents for Meta-Learning over Distributed Databases, Proceedings of the Third International Conference on Knowledge Discovery and Data Mining, AAAI Press, Menlo Park, California, 1997.
	17	R. Subramonian and S. Parthasarathy, An Architecture for Distributed Data Mining, to appear.
	18	The Terabyte Challenge, http://www.ncdm.uic.edu/tc
	19	R. L. Grossman and A. Turinsky, Optimal Strategies for Distributed Data Mining using Data and Model Partitions, submitted for publication.
	20	David H. Wolpert, Stacked generalization, Neural Networks, v.5 n.2, p.241-259, 1992 [doi>10.1016/S0893-6080(05)80023-1]
	21	L. Xu, and M.I. Jordan, EMLearning on A Generalised Finite Mixture Model for Combining Multiple Classifiers, in Proceedings of World Congress on Neural Networks, Hillsdale, New Jersey, Erlbaum, 1993.

CITED BY 12

	Robert Grossman , Robert Hollebeek, The national scalable cluster project: three lessons about high performance data mining and data intensive computing, Handbook of massive data sets, Kluwer Academic Publishers, Norwell, MA, 2002
	Vipin Kumar , Mohammed Zaki, High performance data mining (tutorial PM-3), Tutorial notes of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining, p.309-425, August 20-23, 2000, Boston, Massachusetts, United States
	Robert L. Grossman , Yunhong Gu , Don Hamelburg , Dave Hanley , Xinwei Hong , Jorge Levera , Dave Lillethun , Marco Mazzucco , Joe Mambretti , Jeremy Weinberger, Experimental studies using photonic data services at IGrid 2002, Future Generation Computer Systems, v.19 n.6, p.945-955, August 2003
	Hang Yu , Ee-Chien Chang, Distributed multivariate regression based on influential observations, Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining, August 24-27, 2003, Washington, D.C.
	Salman Alsairafi , Filippia-Sofia Emmanouil , Moustafa Ghanem , Nikolaos Giannadakis , Yike Guo , Dimitrios Kalaitzopoulos , Michelle Osmond , Anthony Rowe , Jameel Syed , Patrick Wendel, The Design of Discovery Net: Towards Open Grid Services for Knowledge Discovery, International Journal of High Performance Computing Applications, v.17 n.3, p.297-315, August 2003
	Robert L. Grossman , Yunhong Gu , Xinwei Hong , Antony Antony , Johan Blom , Freek Dijkstra , Cees de Laat, Teraflows over Gigabit WANs with UDT, Future Generation Computer Systems, v.21 n.4, p.501-513, April 2005
	Marco Mazzucco , Asvin Ananthanarayan , Robert L. Grossman , Jorge Levera , Gokulnath Bhagavantha Rao, Merging multiple data streams on common keys over high performance networks, Proceedings of the 2002 ACM/IEEE conference on Supercomputing, p.1-12, November 16, 2002, Baltimore, Maryland
	Jiewen Luo , Maoguang Wang , Jun Hu , Zhongzhi Shi, Distributed data mining on agent grid: issues, platform and development toolkit, Future Generation Computer Systems, v.23 n.1, p.61-68, January 2007
	Josenildo Costa da Silva , Matthias Klusch , Stefano Lodi , Gianluca Moro, Privacy-preserving agent-based distributed data clustering, Web Intelligence and Agent System, v.4 n.2, p.221-238, April 2006
	L. K. Wickramasinghe , L. D. Alahakoon, Dynamic self organizing maps for discovery and sharing of knowledge in multi agent systems, Web Intelligence and Agent System, v.3 n.1, p.31-47, January 2005
	Jan Tozicka , Michael Rovatsos , Michal Pechoucek, A framework for agent-based distributed machine learning and data mining, Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems, May 14-18, 2007, Honolulu, Hawaii
	Malcolm P. Atkinson , Jano I. van Hemert , Liangxiu Han , Ally Hume , Chee Sun Liew, A distributed architecture for data mining and integration, Proceedings of the second international workshop on Data-aware distributed computing, p.11-20, June 09-10, 2009, Garching, Germany