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Ubiquitous Mining with Interactive Data Mining Agents

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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.

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Authors and Affiliations

  1. School of Computer Science and Information Engineering, Hefei University of Technology, Hefei, 230009, China

    Xin-Dong Wu (Senior Member, IEEE)

  2. Department of Computer Science, University of Vermont, Burlington, VT, 05405, U.S.A.

    Xin-Dong Wu (Senior Member, IEEE) & Qi-Jun Chen

  3. Faculty of Engineering and Information Technology, University of Technology, Sydney, NSW, 2007, Australia

    Xing-Quan Zhu (Member, ACM, IEEE)

  4. Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China

    Fei-Yue Wang (Member, ACM, Fellow, IEEE)

Authors
  1. Xin-Dong Wu
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  2. Xing-Quan Zhu
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  3. Qi-Jun Chen
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  4. Fei-Yue Wang
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Corresponding author

Correspondence to Xin-Dong Wu.

Additional information

This research has been supported by the National Basic Research 973 Program of China under Grant No. 2009CB326203, the National Natural Science Foundation of China under Grant Nos. 60828005 and 60674109, and the Chinese Academy of Sciences under International Partnership Grant No. 2F05N01.

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Wu, XD., Zhu, XQ., Chen, QJ. et al. Ubiquitous Mining with Interactive Data Mining Agents. J. Comput. Sci. Technol. 24, 1018–1027 (2009). https://doi.org/10.1007/s11390-009-9291-7

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  • DOI: https://doi.org/10.1007/s11390-009-9291-7

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