Ubiquitous mining with interactive data mining agents

Wu, XD; Zhu, XQ; Chen, QJ; Wang, FY

Ubiquitous mining with interactive data mining agents

Wu, XD Zhu, XQ Chen, QJ Wang, FY

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Publication Type:: Journal Article
Citation:: Journal of Computer Science and Technology, 2009, 24 (6), pp. 1018 - 1027
Issue Date:: 2009-11-01

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Field	Value	Language
dc.contributor.author	Wu, XD	en_US
dc.contributor.author	Zhu, XQ	en_US
dc.contributor.author	Chen, QJ	en_US
dc.contributor.author	Wang, FY	en_US
dc.date.issued	2009-11-01	en_US
dc.identifier.citation	Journal of Computer Science and Technology, 2009, 24 (6), pp. 1018 - 1027	en_US
dc.identifier.issn	1000-9000	en_US
dc.identifier.uri	http://hdl.handle.net/10453/8920
dc.description.abstract	Due to the increasing availability and sophistication of data recording techniques, multiple information sources and distributed computing are becoming the important trends of modern information systems. Many applications such as security informatics and social computing require a ubiquitous data analysis platform so that decisions can be made rapidly under distributed and dynamic system environments. Although data mining has now been popularly used to achieve such goals, building a data mining system is, however, a nontrivial task, which may require a complete understanding on numerous data mining techniques as well as solid programming skills. Employing agent techniques for data analysis thus becomes increasingly important, especially for users not familiar with engineering and computational sciences, to implement an effective ubiquitous mining platform. Such data mining agents should, in practice, be intelligent, complete, and compact. In this paper, we present an interactive data mining agent - OIDM (online interactive data mining), which provides three categories (classification, association analysis, and clustering) of data mining tools, and interacts with the user to facilitate the mining process. The interactive mining is accomplished through interviewing the user about the data mining task to gain efficient and intelligent data mining control. OIDM can help users find appropriate mining algorithms, refine and compare the mining process, and finally achieve the best mining results. Such interactive data mining agent techniques provide alternative solutions to rapidly deploy data mining techniques to broader areas of data intelligence and knowledge informatics. © 2009 Springer.	en_US
dc.relation.ispartof	Journal of Computer Science and Technology	en_US
dc.relation.isbasedon	10.1007/s11390-009-9291-7	en_US
dc.subject.classification	Software Engineering	en_US
dc.title	Ubiquitous mining with interactive data mining agents	en_US
dc.type	Journal Article
utslib.citation.volume	6	en_US
utslib.citation.volume	24	en_US
utslib.for	0899 Other Information and Computing Sciences	en_US
utslib.for	08 Information and Computing Sciences	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - AAI - Advanced Analytics Institute Research Centre
utslib.copyright.status	closed_access
pubs.issue	6	en_US
pubs.publication-status	Published	en_US
pubs.volume	24	en_US

Abstract:

Due to the increasing availability and sophistication of data recording techniques, multiple information sources and distributed computing are becoming the important trends of modern information systems. Many applications such as security informatics and social computing require a ubiquitous data analysis platform so that decisions can be made rapidly under distributed and dynamic system environments. Although data mining has now been popularly used to achieve such goals, building a data mining system is, however, a nontrivial task, which may require a complete understanding on numerous data mining techniques as well as solid programming skills. Employing agent techniques for data analysis thus becomes increasingly important, especially for users not familiar with engineering and computational sciences, to implement an effective ubiquitous mining platform. Such data mining agents should, in practice, be intelligent, complete, and compact. In this paper, we present an interactive data mining agent - OIDM (online interactive data mining), which provides three categories (classification, association analysis, and clustering) of data mining tools, and interacts with the user to facilitate the mining process. The interactive mining is accomplished through interviewing the user about the data mining task to gain efficient and intelligent data mining control. OIDM can help users find appropriate mining algorithms, refine and compare the mining process, and finally achieve the best mining results. Such interactive data mining agent techniques provide alternative solutions to rapidly deploy data mining techniques to broader areas of data intelligence and knowledge informatics. © 2009 Springer.

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http://hdl.handle.net/10453/8920