Ubiquitous Mining with Interactive Data Mining Agents

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dc.contributor.author Wu, Xindong en_US
dc.contributor.author Zhu, Xingquan en_US
dc.contributor.author Chen, Qijun en_US
dc.contributor.author Wang, Fei-Yue en_US
dc.contributor.editor en_US
dc.date.accessioned 2010-05-28T09:46:22Z
dc.date.available 2010-05-28T09:46:22Z
dc.date.issued 2009 en_US
dc.identifier 2009001761 en_US
dc.identifier.citation Wu Xindong et al. 2009, 'Ubiquitous Mining with Interactive Data Mining Agents', Science China Press, vol. 24, no. 6, pp. 1018-1027. en_US
dc.identifier.issn 1000-9000 en_US
dc.identifier.other C1 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 a?? 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. en_US
dc.language en_US
dc.publisher Science China Press en_US
dc.relation.isbasedon http://dx.doi.org/10.1007/s11390-009-9291-7 en_US
dc.title Ubiquitous Mining with Interactive Data Mining Agents en_US
dc.parent Journal Of Computer Science And Technology en_US
dc.journal.volume 24 en_US
dc.journal.number 6 en_US
dc.publocation Beijing en_US
dc.identifier.startpage 1018 en_US
dc.identifier.endpage 1027 en_US
dc.cauo.name FEIT.Faculty of Engineering & Information Technology en_US
dc.conference Verified OK en_US
dc.for 089900 en_US
dc.personcode 100507 en_US
dc.personcode 107283 en_US
dc.personcode 0000059254 en_US
dc.personcode 0000059255 en_US
dc.percentage 100 en_US
dc.classification.name Other Information and Computing Sciences en_US
dc.classification.type FOR-08 en_US
dc.edition en_US
dc.custom en_US
dc.date.activity en_US
dc.location.activity en_US
dc.description.keywords information systems - human-centered computing - data mining - intelligent agents en_US
dc.staffid en_US


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