Skip to main content
SpringerLink
Log in

VCCM Mining: Mining Virtual Community Core Members Based on Gene Expression Programming

  • Conference paper
Intelligence and Security Informatics (WISI 2006)

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

Included in the following conference series:

Abstract

Intelligence operation against the terrorist network has been studied extensively with the aim to mine the clues and traces of terrorists. The contributions of this paper include: (1) introducing a new approach to classify terrorists based on Gene Expression Programming (GEP); (2) analyzing the characteristics of the terrorist organization, and proposing an algorithm called Create Virtual Community (CVC) based on tree-structure to create a virtual community; (3) proposing a formal definition of Virtual Community (VC) and the VCCM Mining algorithm to mine the core members of a virtual community. Experimental results demonstrate the effectiveness of VCCM Mining.

This work was supported by National Science Foundation of China (60473071), Specialized Research Fund for Doctoral Program by the Ministry of Education (20020610007).

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Wentz, L.K., Lee, W.: Wagenhals:Effects Based Operations for Transnational Terrorist Organizations: Assessing Alternative Courses of Action to Mitigate Terrorist Threats. In: Proceedings of Command and Control Research and Technology Symposium, San Diego (2004)

    Google Scholar 

  2. Zhou, C., Xiao, W., Nelson, P.C., Tirpak, T.M.: Evolving Accurate and Compact Classification Rules with Gene Expression Programming. IEEE Transactions on Evolutionary Computation 7(6), 519–531 (2003)

    Article  Google Scholar 

  3. Ferreira, C.: Gene Expression Programming: Mathematical Modeling by an Artificial Intelligence, Angra do Heroismo, Portugal (2002)

    Google Scholar 

  4. Matt Crenson: Math wizards offer help in fighting terrorism (2004), http://www.azstarnet.com/dailystar/relatedarticles/42692.php

  5. Qiao, S., Tang, C., Yu, Z., Wei, J., Li, H., Wu, L.: Mining Virtual Community Structure Based on SVM. Computer Science 32(7), 208–212 (2005)

    Google Scholar 

  6. Peng, J., Tang, C., Zhang, J., Yuan, C.: Evolutionary Algorithm Based on Overlapped Gene Expression. In: Wang, L., Chen, K., S. Ong, Y. (eds.) ICNC 2005. LNCS, vol. 3612, pp. 194–204. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  7. Ferreira, C.: Gene Expression Programming in Problem Solving. Soft Computing and Industry: Recent Applications, pp. 635–654. Springer, Heidelberg (2002)

    Google Scholar 

  8. Platt, J.: Sequential minimal optimization: A fast algorithm for training support vector machines. Advances in Kernel Methods-Support Vector learning, pp. 185–208. MIT Press, Cambridge (1999)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Computer Science and Engineering, Sichuan University, Chengdu, 610065, China

    Shaojie Qiao, Changjie Tang, Jing Peng & Yong Xiang

  2. Department of Computer Science and Software Engineering, the University of Melbourne, Australia

    Hongjian Fan

Authors
  1. Shaojie Qiao
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Changjie Tang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jing Peng
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Hongjian Fan
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Yong Xiang
    View author publications

    You can also search for this author in PubMed Google Scholar

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

Rights and permissions

Reprints and permissions

Copyright information

© 2006 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Qiao, S., Tang, C., Peng, J., Fan, H., Xiang, Y. (2006). VCCM Mining: Mining Virtual Community Core Members Based on Gene Expression Programming. 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_16

Download citation

  • DOI: https://doi.org/10.1007/11734628_16

  • 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)

Publish with us

Policies and ethics

Search

Navigation