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Discovering Investigation Clues through Mining Criminal Databases

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Intelligence and Security Informatics

Part of the book series: Studies in Computational Intelligence ((SCI,volume 135))

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Abstract

The law enforcement holds a large quantity of data that are records of official operations or private materials of the people. These data can be used for increasing benefits of the people or enhancing the efficiency of governmental operations. Data mining is one of the emerging techniques to manipulate huge amount of data. In this paper we will apply to this technique to the data of stolen automobiles to explore the unknown knowledge hidden in the data and provide this knowledge to transportation, insurance as well as police agencies for decision supports. The data we use are abstracted from 378 thousand records of stolen automobiles in the past eleven years in Taiwan. After constructing a data warehouse, we apply to the technique of classification, clustering, association rule, prediction, data generalization and summarization-based characterization to discover new knowledge. Our results include the understanding of automobile theft, possibility of finding stolen automobiles, intrigue in theft claims, etc. The knowledge we acquired is useful in decision support, showing the applicability of data mining in public affairs. The experience we gathered in this study would help the use of this technique in other public sectors. Along with the research results, we suggest the law enforcement to consider data mining as a new means to investigate criminal cases, to set up a team of criminal data analysis, to launch a new program to crack down automobile thefts, and to improve the quality of criminal data.

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Authors and Affiliations

  1. Center for Strategic and Industrial Studies, Dept of Information Management, Tatung University, Taiwan

    Patrick S. Chen

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  1. Patrick S. Chen
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Hsinchun Chen Christopher C. Yang

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Chen, P.S. (2008). Discovering Investigation Clues through Mining Criminal Databases. In: Chen, H., Yang, C.C. (eds) Intelligence and Security Informatics. Studies in Computational Intelligence, vol 135. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69209-6_10

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  • DOI: https://doi.org/10.1007/978-3-540-69209-6_10

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-69207-2

  • Online ISBN: 978-3-540-69209-6

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