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
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