Bayesian inferential reasoning model for crime investigation

Jing Wang, Zhijie Xu

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

1 Citation (Scopus)

Abstract

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.

Original languageEnglish
Title of host publicationSmart Digital Futures 2014
PublisherIOS Press
Pages59-67
Number of pages9
Volume262
ISBN (Print)9781614994046
DOIs
Publication statusPublished - 2014

Publication series

NameFrontiers in Artificial Intelligence and Applications
Volume262
ISSN (Print)09226389

Fingerprint

Crime
Bayesian networks
DNA
Visualization
Decision making
Testing
Experiments

Cite this

Wang, J., & Xu, Z. (2014). Bayesian inferential reasoning model for crime investigation. In Smart Digital Futures 2014 (Vol. 262, pp. 59-67). (Frontiers in Artificial Intelligence and Applications; Vol. 262). IOS Press. https://doi.org/10.3233/978-1-61499-405-3-59
Wang, Jing ; Xu, Zhijie. / Bayesian inferential reasoning model for crime investigation. Smart Digital Futures 2014. Vol. 262 IOS Press, 2014. pp. 59-67 (Frontiers in Artificial Intelligence and Applications).
@inproceedings{25ff7a836a9b4dcca1f587250af3525c,
title = "Bayesian inferential reasoning model for crime investigation",
abstract = "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.",
keywords = "Bayesian Networks, Digitised Forensic Evidence, Inferential Reasoning",
author = "Jing Wang and Zhijie Xu",
year = "2014",
doi = "10.3233/978-1-61499-405-3-59",
language = "English",
isbn = "9781614994046",
volume = "262",
series = "Frontiers in Artificial Intelligence and Applications",
publisher = "IOS Press",
pages = "59--67",
booktitle = "Smart Digital Futures 2014",
address = "Netherlands",

}

Wang, J & Xu, Z 2014, Bayesian inferential reasoning model for crime investigation. in Smart Digital Futures 2014. vol. 262, Frontiers in Artificial Intelligence and Applications, vol. 262, IOS Press, pp. 59-67. https://doi.org/10.3233/978-1-61499-405-3-59

Bayesian inferential reasoning model for crime investigation. / Wang, Jing; Xu, Zhijie.

Smart Digital Futures 2014. Vol. 262 IOS Press, 2014. p. 59-67 (Frontiers in Artificial Intelligence and Applications; Vol. 262).

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

TY - GEN

T1 - Bayesian inferential reasoning model for crime investigation

AU - Wang, Jing

AU - Xu, Zhijie

PY - 2014

Y1 - 2014

N2 - 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.

AB - 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.

KW - Bayesian Networks

KW - Digitised Forensic Evidence

KW - Inferential Reasoning

UR - http://www.scopus.com/inward/record.url?scp=84902328767&partnerID=8YFLogxK

U2 - 10.3233/978-1-61499-405-3-59

DO - 10.3233/978-1-61499-405-3-59

M3 - Conference contribution

SN - 9781614994046

VL - 262

T3 - Frontiers in Artificial Intelligence and Applications

SP - 59

EP - 67

BT - Smart Digital Futures 2014

PB - IOS Press

ER -

Wang J, Xu Z. Bayesian inferential reasoning model for crime investigation. In Smart Digital Futures 2014. Vol. 262. IOS Press. 2014. p. 59-67. (Frontiers in Artificial Intelligence and Applications). https://doi.org/10.3233/978-1-61499-405-3-59