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Rule+Exception Learning-Based Class Specification and Labeling in Intelligence and Security Analysis

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Intelligence and Security Informatics (WISI 2006)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 3917))

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Abstract

One of the key tasks in intelligence and security informatics (ISI) is to find anomalies and exceptions from typically voluminous datasets and observations [1-4]. For example, in the context of societal security, finding “exceptions” may involve discovering irregular behaviors in a community where it is assumed that most people behave normally.

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References

  1. Chen, H., Wang, F.Y.: Artificial Intelligence for Homeland Security. IEEE Intelligent Systems, pp. 12-16 (2005)

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  2. Chen, H., Wang, F.Y., Zeng, D.: Intelligence and Security informatics for Homeland Security: Information, Communication and Transportation. IEEE Trans. Intelligent Transportation Systems, pp. 329-341 (2004)

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  3. Kantor, P., Muresan, G., Roberts, F., Zeng, D., Wang, F.Y., Chen, H., Merkle, R.C.: Intelligence and Security Informatics. In: Proceedings IEEE Conference on Intelligence and Security informatics, Atlanta, GA,USA (May 2005)

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  4. Yao, Y.Y., Wang, F.Y., Wang, J., Zeng, D.: Rule + Exception Strategies for Security Information Analysis. IEEE Intelligent Systems, 52–57 (2005)

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Author information

Authors and Affiliations

  1. Chinese Academy of Sciences, Beijing, 100080, China

    Jue Wang & Fei-Yue Wang

  2. University of Arizona, Tucson, Arizona, 85721, USA

    Daniel D. Zeng

Authors
  1. Jue Wang
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  2. Fei-Yue Wang
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  3. Daniel D. Zeng
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Editor information

Editors and Affiliations

  1. Department of Management Information Systems, Eller College of Management, The University of Arizona, 85721, AZ, USA

    Hsinchun Chen

  2. Chinese Academy of Sciences, 100190, Beijing, China

    Fei-Yue Wang

  3. Drexel University, 19104, Philadelphia, PA, USA

    Christopher C. Yang

  4. MIS Department, University of Arizona, and Chinese Academy of Sciences, Tucson, AZ, USA

    Daniel Zeng

  5. The University of Hong Kong, Hong Kong, China

    Michael Chau

  6. School of Computer Engineering, Nanyang Technological University, 639798, Singapore

    Kuiyu Chang

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© 2006 Springer-Verlag Berlin Heidelberg

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Wang, J., Wang, FY., Zeng, D.D. (2006). Rule+Exception Learning-Based Class Specification and Labeling in Intelligence and Security Analysis. In: Chen, H., Wang, FY., Yang, C.C., Zeng, D., Chau, M., Chang, K. (eds) Intelligence and Security Informatics. WISI 2006. Lecture Notes in Computer Science, vol 3917. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11734628_32

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  • DOI: https://doi.org/10.1007/11734628_32

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-33361-6

  • Online ISBN: 978-3-540-33362-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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