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Three Big Data Case Studies

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Guide to Computational Modelling for Decision Processes

Part of the book series: Simulation Foundations, Methods and Applications ((SFMA))

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Abstract

The utilisation of Big Data within the criminology field has allowed a revaluation of the traditional assessment and investigation of available data sources, pushing criminological research towards new frontiers. However, the enormous amount of data, which is now available from numerous sources focusing on criminology, has created both challenges and opportunities in the discovery of innovative approaches to prevent, detect and predict crime.

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References

  1. Trovati M, Bessis N (2015) An influence assessment method based on co-occurrence for topologically reduced big data sets. Soft Computing

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Author information

Authors and Affiliations

  1. Department of Computer Science, Edge Hill University, Ormskirk, L39 4QP, UK

    Marcello Trovati

  2. College of Engineering and Technology, University of Derby, Kedleston Road, Derby, DE22 1GB, UK

    Andy Baker

Authors
  1. Marcello Trovati
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  2. Andy Baker
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Corresponding author

Correspondence to Marcello Trovati .

Editor information

Editors and Affiliations

  1. Department of Computing and Mathematics, College of Engineering and Technology, University of Derby, Derby, United Kingdom

    Stuart Berry

  2. University of Derby, Derby, United Kingdom

    Val Lowndes

  3. University of Derby, Derby, United Kingdom

    Marcello Trovati

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Trovati, M., Baker, A. (2017). Three Big Data Case Studies. In: Berry, S., Lowndes, V., Trovati, M. (eds) Guide to Computational Modelling for Decision Processes. Simulation Foundations, Methods and Applications. Springer, Cham. https://doi.org/10.1007/978-3-319-55417-4_15

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  • DOI: https://doi.org/10.1007/978-3-319-55417-4_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-55416-7

  • Online ISBN: 978-3-319-55417-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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