Bayesian inferential reasoning model for crime investigation

WANG, Jing and XU, Zhijie (2014). Bayesian inferential reasoning model for crime investigation. In: NEVES-SILVA, Rui, TSHIRINTZIS, George A. and USKOV, Vladimir, (eds.) Smart digital futures 2014. Frontiers in Artificial Intelligence and Applications (262). IOS Press, 59-67.

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Forensic inferential reasoning is a “fact-finding” journey for crime investigation and evidence presentation. In complex legal practices involving various forms of evidence, conventional decision making processes based on human intuition and piece-to-piece evidence explanation often fail to reconstruct meaningful and convincing legal hypothesis. It is necessary to develop logical system for evidence management and relationship evaluations. In this paper, a forensic application-oriented inferential reasoning model has been devised base on Bayesian Networks. It provides an effective approach to identify and evaluate possible relationships among different evidence. The model has been developed into an adaptive framework than can be further extended to support information visualisation and interaction. Based on the system experiments, the model has been successfully used in verifying the logical relationships between DNA testing results and confessions acquired from the suspect in a simulated criminal investigation, which provided a firm foundation for the future developments.

Item Type: Book Section
Additional Information: Paper originally presented at the 6th International Conference on Intelligent Decision Technologies (KES IDT 2014) Chania, Greece. 18 - 20 June 2014.
Departments - Does NOT include content added after October 2018: Faculty of Science, Technology and Arts > Department of Computing
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Page Range: 59-67
Depositing User: Jing Wang
Date Deposited: 26 Mar 2018 10:58
Last Modified: 18 Mar 2021 15:20

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