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

Created by W.Langdon from gp-bibliography.bib Revision:1.4549

  author =       "Shaojie Qiao and Changjie Tang and Jing Peng and 
                 Hongjian Fan and Yong Xiang",
  title =        "{VCCM} Mining: Mining Virtual Community Core Members
                 Based on Gene Expression Programming",
  year =         "2006",
  bibdate =      "2006-03-15",
  bibsource =    "DBLP,
  pages =        "133--138",
  booktitle =    "Proceedings of Intelligence and Security Informatics:
                 International Workshop, WISI 2006",
  editor =       "Hsinchun Chen and Fei Yue Wang and 
                 Christopher C. Yang and Daniel Zengand Michael Chau and Kuiyu Chang",
  volume =       "3917",
  series =       "Lecture Notes in Computer Science",
  address =      "Singapore",
  month =        apr # " 9",
  publisher =    "Springer",
  keywords =     "genetic algorithms, genetic programming, Gene
                 Expression Programming",
  ISBN =         "3-540-33361-4",
  DOI =          "doi:10.1007/11734628_16",
  size =         "6 pages",
  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) analysing the characteristics of
                 the terrorist organisation, 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), Specialised Research Fund for
                 Doctoral Program by the Ministry of Education

Genetic Programming entries for Shaojie Qiao Changjie Tang Jing Peng Hongjian Fan Yong Xiang