A novel approach for intelligent crime pattern discovery and prediction

K. R.Sai Vineeth, Ayush Pandey, Tribikram Pradhan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

'Crime analysis plays a major part in crime prevention and safety of people in a country. The paper focuses on state based frequent crime pattern knowledge discovery and prevention. Our work concentrates on Finding frequent crimes state wise using FP Max a bottom up approach which uses linked lists for reduction of space complexity. The generated frequent crime sets of state will be undergone through knowledge discovery process. Correlation between the crime types is done to find the weightage factor of crime types to find crime intensity point. The crime intensity point of 29 states and 7 union territories are calculated according to the weightages derived from the correlation analysis. Later we classified the states as most dangerous, dangerous, moderate or safe based on their crime intensity point using Random forests classification technique. Prediction of crime intensity point for the state based on the responsible factors that contribute to a crime.

Original languageEnglish
Title of host publicationProceedings of 2016 International Conference on Advanced Communication Control and Computing Technologies, ICACCCT 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages531-538
Number of pages8
ISBN (Electronic)9781467395458
DOIs
Publication statusPublished - 24-01-2017
Event2016 International Conference on Advanced Communication Control and Computing Technologies, ICACCCT 2016 - Ramanathapuram, Tamil Nadu, India
Duration: 25-05-201627-05-2016

Conference

Conference2016 International Conference on Advanced Communication Control and Computing Technologies, ICACCCT 2016
CountryIndia
CityRamanathapuram, Tamil Nadu
Period25-05-1627-05-16

Fingerprint

Crime
Data mining

All Science Journal Classification (ASJC) codes

  • Hardware and Architecture
  • Signal Processing
  • Computer Networks and Communications
  • Computer Science Applications

Cite this

Vineeth, K. R. S., Pandey, A., & Pradhan, T. (2017). A novel approach for intelligent crime pattern discovery and prediction. In Proceedings of 2016 International Conference on Advanced Communication Control and Computing Technologies, ICACCCT 2016 (pp. 531-538). [7831697] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICACCCT.2016.7831697
Vineeth, K. R.Sai ; Pandey, Ayush ; Pradhan, Tribikram. / A novel approach for intelligent crime pattern discovery and prediction. Proceedings of 2016 International Conference on Advanced Communication Control and Computing Technologies, ICACCCT 2016. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 531-538
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Vineeth, KRS, Pandey, A & Pradhan, T 2017, A novel approach for intelligent crime pattern discovery and prediction. in Proceedings of 2016 International Conference on Advanced Communication Control and Computing Technologies, ICACCCT 2016., 7831697, Institute of Electrical and Electronics Engineers Inc., pp. 531-538, 2016 International Conference on Advanced Communication Control and Computing Technologies, ICACCCT 2016, Ramanathapuram, Tamil Nadu, India, 25-05-16. https://doi.org/10.1109/ICACCCT.2016.7831697

A novel approach for intelligent crime pattern discovery and prediction. / Vineeth, K. R.Sai; Pandey, Ayush; Pradhan, Tribikram.

Proceedings of 2016 International Conference on Advanced Communication Control and Computing Technologies, ICACCCT 2016. Institute of Electrical and Electronics Engineers Inc., 2017. p. 531-538 7831697.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Vineeth KRS, Pandey A, Pradhan T. A novel approach for intelligent crime pattern discovery and prediction. In Proceedings of 2016 International Conference on Advanced Communication Control and Computing Technologies, ICACCCT 2016. Institute of Electrical and Electronics Engineers Inc. 2017. p. 531-538. 7831697 https://doi.org/10.1109/ICACCCT.2016.7831697