• DocumentCode
    2350751
  • Title

    Concept Discovery Innovations in Law Enforcement: A Perspective

  • Author

    Poelmans, Jonas ; Elzinga, Paul ; Viaene, Stijn ; Dedene, Guido

  • Author_Institution
    Fac. of Bus. & Econ., K.U. Leuven, Leuven, Belgium
  • fYear
    2010
  • fDate
    24-26 Nov. 2010
  • Firstpage
    473
  • Lastpage
    478
  • Abstract
    In the past decades, the amount of information available to law enforcement agencies has increased significantly. Most of this information is in textual form, however analyses have mainly focused on the structured data. In this paper, we give an overview of the concept discovery projects at the Amsterdam-Amstell and police where Formal Concept Analysis (FCA) is being used as text mining instrument. FCA is combined with statistical techniques such as Hidden Markov Models (HMM) and Emergent Self Organizing Maps (ESOM). The combination of this concept discovery and refinement technique with statistical techniques for analyzing high-dimensional data not only resulted in new insights but often in actual improvements of the investigation procedures.
  • Keywords
    data mining; data structures; formal concept analysis; hidden Markov models; law administration; self-organising feature maps; statistical analysis; text analysis; Amsterdam-Amstell; concept discovery innovation; concept discovery projects; emergent self organizing maps; formal concept analysis; hidden Markov models; law enforcement; statistical techniques; structured data; text mining instrument; textual form information; Formal Concept Analysis; Intelligence Led Policing; knowledge discovery;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Networking and Collaborative Systems (INCOS), 2010 2nd International Conference on
  • Conference_Location
    Thessaloniki
  • Print_ISBN
    978-1-4244-8828-5
  • Electronic_ISBN
    978-1-4244-4278-2
  • Type

    conf

  • DOI
    10.1109/INCOS.2010.18
  • Filename
    5702145