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
Link To Document :
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