Domain-Driven, Actionable Knowledge Discovery

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	Similar Articles Articles by Longbing Cao Articles by Chengqi Zhang Articles by Qiang Yang Articles by David Bell Articles by Michail Vlachos Articles by Bahar Taneri Articles by Eamonn Keogh Articles by Philip S. Yu Articles by Ning Zhong Articles by Mafruz Zaman Ashrafi Articles by David Taniar Articles by Eugene Dubossarsky Articles by Warwick Graco

July/August 2007 (vol. 22 no. 4)

pp. 78-88, c3

	ASCII Text	x
	Longbing Cao, Chengqi Zhang, Qiang Yang, David Bell, Michail Vlachos, Bahar Taneri, Eamonn Keogh, Philip S. Yu, Ning Zhong, Mafruz Zaman Ashrafi, David Taniar, Eugene Dubossarsky, Warwick Graco, "Domain-Driven, Actionable Knowledge Discovery," IEEE Intelligent Systems, vol. 22, no. 4, pp. 78-88, c3, July/August, 2007.

	BibTex	x
	@article{ 10.1109/MIS.2007.67, author = {Longbing Cao and Chengqi Zhang and Qiang Yang and David Bell and Michail Vlachos and Bahar Taneri and Eamonn Keogh and Philip S. Yu and Ning Zhong and Mafruz Zaman Ashrafi and David Taniar and Eugene Dubossarsky and Warwick Graco}, title = {Domain-Driven, Actionable Knowledge Discovery}, journal ={IEEE Intelligent Systems}, volume = {22}, number = {4}, issn = {1541-1672}, year = {2007}, pages = {78-88, c3}, doi = {http://doi.ieeecomputersociety.org/10.1109/MIS.2007.67}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - MGZN JO - IEEE Intelligent Systems TI - Domain-Driven, Actionable Knowledge Discovery IS - 4 SN - 1541-1672 SP78 EP88, c3 EPD - 78-88, c3 A1 - Longbing Cao, A1 - Chengqi Zhang, A1 - Qiang Yang, A1 - David Bell, A1 - Michail Vlachos, A1 - Bahar Taneri, A1 - Eamonn Keogh, A1 - Philip S. Yu, A1 - Ning Zhong, A1 - Mafruz Zaman Ashrafi, A1 - David Taniar, A1 - Eugene Dubossarsky, A1 - Warwick Graco, PY - 2007 KW - data mining KW - data models KW - database searching KW - knowledge engineering KW - visualization VL - 22 JA - IEEE Intelligent Systems ER -

Longbing Cao, University of Technology, Sydney

Chengqi Zhang, University of Technology, Sydney

Qiang Yang, Hong Kong University of Science and Technology

David Bell, Queen's University Belfast

Michail Vlachos, IBM T.J. Watson Research Center

Bahar Taneri, Scripps Genome Center

Eamonn Keogh, University of California, Riverside

Philip S. Yu, IBM Thomas J. Watson Research Center

Ning Zhong, Maebashi Institute of Technology

Mafruz Zaman Ashrafi, Institute for Infocomm Research

David Taniar, Monash University

Eugene Dubossarsky, Ernst & Young

Warwick Graco, Australian Taxation Office

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/MIS.2007.67

Existing knowledge discovery and data mining (KDD) field seldom deliver results that businesses can act on directly. This issue, Trends & Controversies presents seven short articles reporting on different aspects of domain-driven KDD, an R&D area that targets the development of effective methodologies and techniques for delivering actionable knowledge in a given domain, especially business.

Index Terms:

data mining, data models, database searching, knowledge engineering, visualization

Citation:

Longbing Cao, Chengqi Zhang, Qiang Yang, David Bell, Michail Vlachos, Bahar Taneri, Eamonn Keogh, Philip S. Yu, Ning Zhong, Mafruz Zaman Ashrafi, David Taniar, Eugene Dubossarsky, Warwick Graco, "Domain-Driven, Actionable Knowledge Discovery," IEEE Intelligent Systems, vol. 22, no. 4, pp. 78-88, c3, July/Aug. 2007, doi:10.1109/MIS.2007.67

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