• DocumentCode
    2290353
  • Title

    CADRE: continuous analysis and discovery from relational evidence

  • Author

    Pioch, Nicholas ; Hunter, Dan ; Fournelle, Connie ; Washburn, B. ; Moore, Kendra ; Jones, Eric ; Bostwick, Dan ; Kao, Amy ; Graham, Stephen ; Allen, Tom ; Dunn, Mike

  • Author_Institution
    Alphatech Inc., Burlington, MA, USA
  • fYear
    2003
  • fDate
    30 Sept.-4 Oct. 2003
  • Firstpage
    555
  • Lastpage
    561
  • Abstract
    CADRE (continuous analysis and discovery from relational evidence) is a link detection system that takes in a threat pattern and partial evidence about threat cases and outputs threat hypotheses with inferred actors and events. CADRE uses a Prolog-based frame system to represent threat patterns and enforce temporal and equality constraints among pattern slots. Based on rules involving uniquely identifying slots in the pattern, CADRE triggers an initial set of threat hypotheses, and then refines these hypotheses by generating queries for unknown slots from constraints involving known slots. To evaluate hypotheses, CADRE scores each local hypothesis using a probabilistic model in order to create a consistent, high-value global hypothesis by pruning conflicting lower scoring hypotheses. In a program-wide first year evaluation using simulated threats, CADRE performed best overall among five participating link detection systems.
  • Keywords
    PROLOG; constraint theory; frame based representation; heuristic programming; knowledge acquisition; military computing; pattern recognition; query formulation; CADRE; Prolog-based frame system; link detection system; pattern slots; probabilistic model; query generation; relational evidence; temporal constraints; threat hypotheses; threat pattern; Artificial intelligence; Data analysis; Event detection; Humans; Information analysis; Intelligent structures; National security; Pattern analysis; Pattern matching; Terrorism;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Integration of Knowledge Intensive Multi-Agent Systems, 2003. International Conference on
  • Print_ISBN
    0-7803-7958-6
  • Type

    conf

  • DOI
    10.1109/KIMAS.2003.1245100
  • Filename
    1245100