Abstract
The growing availability of information technologies has enabled law enforcement agencies to collect detailed data about various crimes. Classification techniques can be applied to these data to build decision-aid tools and facilitate investigations of law enforcement agencies. In this paper, we propose an approach for constructing a decision tree based classification model for a crime prediction. Proposed model assists law enforcement agencies in discovering crime patterns and predicting future trends. We provide an implementation and analysis of our proposed method.
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Acknowledgments
This work was supported by the IT R&D program of MKE/KEIT. [10041854, Development of a smart home service platform with real-time danger prediction and prevention for safety residential environments].
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© 2013 Springer Science+Business Media Dordrecht
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Nasridinov, A., Ihm, SY., Park, YH. (2013). A Decision Tree-Based Classification Model for Crime Prediction. In: Park, J.J., Barolli, L., Xhafa, F., Jeong, H.Y. (eds) Information Technology Convergence. Lecture Notes in Electrical Engineering, vol 253. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-6996-0_56
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DOI: https://doi.org/10.1007/978-94-007-6996-0_56
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