Show simple item record Shen, Qiang Keppens, Jeroen Aitken, Colin Schafer, Burkhard Lee, Mark 2008-01-23T12:13:52Z 2008-01-23T12:13:52Z 2007-01-16
dc.identifier.citation Shen , Q , Keppens , J , Aitken , C , Schafer , B & Lee , M 2007 , ' A scenario-driven decision support system for serious crime investigation ' Law, Probability and Risk , vol 5 , no. 2 , pp. 87-117 . DOI: 10.1093/lpr/mgl014 en
dc.identifier.issn 1470-8396
dc.identifier.other PURE: 74378
dc.identifier.other PURE UUID: 18443db0-4280-4e32-ba70-816a5bc442cf
dc.identifier.other dspace: 2160/464
dc.identifier.other DSpace_20121128.csv: row: 323
dc.description Q. Shen, J. Keppens, C. Aitken, B. Schafer, and M. Lee. A scenario driven decision support system for serious crime investigation. Law, Probability and Risk, 5(2):87-117, 2006. Sponsorship: UK Engineering and Physical Sciences Research Council grant GR/S63267; partially supported by grant GR/S98603 en
dc.description.abstract Consideration of a wide range of plausible crime scenarios during any crime investigation is important to seek convincing evidence and hence to minimize the likelihood of miscarriages of justice. It is equally important for crime investigators to be able to employ effective and efficient evidence-collection strategies that are likely to produce the most conclusive information under limited available resources. An intelligent decision support system that can assist human investigators by automatically constructing plausible scenarios, and reasoning with the likely best investigating actions will clearly be very helpful in addressing these challenging problems. This paper presents a system for creating scenario spaces from given evidence, based on an integrated application of techniques for compositional modelling and Bayesian network-based evidence evaluation. Methods of analysis are also provided by the use of entropy to exploit the synthesized scenario spaces in order to prioritize investigating actions and hypotheses. These theoretical developments are illustrated by realistic examples of serious crime investigation. en
dc.format.extent 31 en
dc.language.iso eng
dc.relation.ispartof Law, Probability and Risk en
dc.rights en
dc.subject crime investigation en
dc.subject decision support en
dc.subject scenario generation en
dc.subject scenario fragments en
dc.subject Bayesian networks en
dc.subject evidence evaluation en
dc.subject conditional independence en
dc.subject system architecture en
dc.subject entropy en
dc.title A scenario-driven decision support system for serious crime investigation en
dc.type /dk/atira/pure/researchoutput/researchoutputtypes/contributiontojournal/article en
dc.contributor.institution Department of Computer Science en
dc.contributor.institution Advanced Reasoning Group en
dc.description.status Peer reviewed en

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