Name
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. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/INCOS.2010.18 | Intelligent Networking and Collaborative Systems |
Keywords | Field | DocType |
hidden markov models,emergent self organizing maps,high-dimensional data,concept discovery innovations,law enforcement,concept discovery,formal concept analysis,statistical technique,investigation procedure,actual improvement,structured data,concept discovery project,statistical analysis,text analysis,data structures,data mining,data visualization,text mining,knowledge discovery,lattices | Data science,Data structure,Data visualization,Computer science,Knowledge extraction,Statistics,Law enforcement,Hidden Markov model,Formal concept analysis,Data model,Intelligence-led policing,Distributed computing | Conference |
ISBN | Citations | PageRank |
978-1-4244-4278-2 | 4 | 0.46 |
References | Authors | |
9 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jonas Poelmans | 1 | 277 | 19.28 |
| Paul Elzinga | 2 | 122 | 9.14 |
| Stijn Viaene | 3 | 722 | 60.17 |
| Guido Dedene | 4 | 925 | 83.39 |