Regular frequent crime pattern mining on crime datasets

  • Authors

    • G Vijay Kumar
    • M Sreedevi
    • G Vamsi Krishna
    • N Sai Ram
    2018-03-18
    https://doi.org/10.14419/ijet.v7i2.7.11438
  • Crime Pattern, Crime Dataset, Regular-Frequent Patterns, Vertical Data.

  • Abstract

    The objective of violation information mining is to comprehend different violation designs in criminal conduct in request to foresee viola-tions and expect criminal movement to stay away from the violation not to happen. Foreseeing violation is one of the worldwide difficulties looking by Law authorization office and it requires tireless endeavors with a specific end goal to limit. In this paper we are presenting anoth-er violation design called general incessant violation design which happens frequently at certain time interims utilizing vertical information arrange additionally fulfills descending conclusion property. Violation designs were not characterized by insights and its distinguishing proof is some-thing other than checking and abridging violations that are comparable in attributes and additionally area on a guide. Violation design is a gathering of at least one violations answered to or on the other hand found by the police.

     

     

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  • How to Cite

    Vijay Kumar, G., Sreedevi, M., Vamsi Krishna, G., & Sai Ram, N. (2018). Regular frequent crime pattern mining on crime datasets. International Journal of Engineering & Technology, 7(2.7), 972-975. https://doi.org/10.14419/ijet.v7i2.7.11438

    Received date: 2018-04-12

    Accepted date: 2018-04-12

    Published date: 2018-03-18