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Pacific-Asia Workshop on Intelligence and Security Informatics

PAISI 2007: Intelligence and Security Informatics pp 311–313Cite as

Mining the Core Member of Terrorist Crime Group Based on Social Network Analysis

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 4430))

Abstract

Since the incident about 9.11, the Security Sectors of many countries have put great attentions on gathering and mining of crime data and establishing anti-terrorist databases. With the emergence of anti-terrorist application, data mining for anti-terrorist has attracted great attention from both researchers and officers as well as in China. The purpose of analyzing and mining related terrorist or crimes data is that analyzing of psychology, behavior and related laws about crime, and providing hidden clues to prevent a criminal case, and forecasting terror happening to keeping with crime limits.

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References

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Author information

Authors and Affiliations

  1. DB&KE Institute, School of Computer, Sichuan University, Chengdu, 610065, China

    Qihong Liu, Changjie Tang, Shaojie Qiao & Fenlian Wen

  2. School of Electric Information, Sichuan University, Chengdu, 610065, China

    Qihong Liu

  3. School of Commonality Administer, Sichuan University, Chengdu, 610065, China

    Qiwei Liu

Authors
  1. Qihong Liu
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  2. Changjie Tang
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  3. Shaojie Qiao
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  4. Qiwei Liu
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  5. Fenlian Wen
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Editor information

Christopher C. Yang Daniel Zeng Michael Chau Kuiyu Chang Qing Yang Xueqi Cheng Jue Wang Fei-Yue Wang Hsinchun Chen

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© 2007 Springer Berlin Heidelberg

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Cite this paper

Liu, Q., Tang, C., Qiao, S., Liu, Q., Wen, F. (2007). Mining the Core Member of Terrorist Crime Group Based on Social Network Analysis. In: Yang, C.C., et al. Intelligence and Security Informatics. PAISI 2007. Lecture Notes in Computer Science, vol 4430. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71549-8_35

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  • DOI: https://doi.org/10.1007/978-3-540-71549-8_35

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-71548-1

  • Online ISBN: 978-3-540-71549-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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