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Using Formal Concepts Analysis Techniques in Mining Data from Criminal Databases and Profiling Events Based on Factors to Understand Criminal Environments

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Book cover Computational Science and Its Applications – ICCSA 2016 (ICCSA 2016)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9790))

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Abstract

As population increases and technological developments advances, criminal activities become complex and sophisticated. Understanding relationships between criminal activities, social factors, geographical locations, crime types, communications links, etc. becomes very crucial. Physical surveillance and other conventional modes of analysis of crime data does not show relationships between direct criminal activity variables and create visualization and interactivity between them. This has yielded difficulties in controlling indirect and direct factors that are likely to provide an environment for such activities. Within this paper, we proposed and engaged Formal Concept Analysis which is based on Galois lattice theory to create relationships between criminal activities, social factors, geographical locations, crime types, communications links, etc. This created a better visualization of relationships between geographical areas and provided a better view in combating crime as well as providing intelligence on the environmental factors based on geography.

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Author information

Authors and Affiliations

  1. Ghana Technology University, Accra, Ghana

    Quist-Aphetsi Kester

  2. Lab-STICC (UMR CNRS 6285), University of Brest, Brest, France

    Quist-Aphetsi Kester

  3. Directorate of Information Assurance and Intelligence Research, CRITAC, Accra, Ghana

    Quist-Aphetsi Kester

  4. Department of Computer Science and Information Technology, University of Cape Coast, Cape Coast, Ghana

    Quist-Aphetsi Kester

Authors
  1. Quist-Aphetsi Kester
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Correspondence to Quist-Aphetsi Kester .

Editor information

Editors and Affiliations

  1. University of Perugia, Perugia, Italy

    Osvaldo Gervasi

  2. University of Basilicata, Potenza, Italy

    Beniamino Murgante

  3. Covenant University, Ota, Nigeria

    Sanjay Misra

  4. University of Minho, Braga, Portugal

    Ana Maria A.C. Rocha

  5. Polytechnic University, Bari, Italy

    Carmelo M. Torre

  6. Monash University, Clayton, Victoria, Australia

    David Taniar

  7. Kyushu Sangyo University, Fukuoka, Japan

    Bernady O. Apduhan

  8. Saint Petersburg State University, Saint Petersburg, Russia

    Elena Stankova

  9. Beijing University of Posts and Telecommunications, Beijing, China

    Shangguang Wang

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Kester, QA. (2016). Using Formal Concepts Analysis Techniques in Mining Data from Criminal Databases and Profiling Events Based on Factors to Understand Criminal Environments. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2016. ICCSA 2016. Lecture Notes in Computer Science(), vol 9790. Springer, Cham. https://doi.org/10.1007/978-3-319-42092-9_37

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  • DOI: https://doi.org/10.1007/978-3-319-42092-9_37

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-42091-2

  • Online ISBN: 978-3-319-42092-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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