Knowledge Based Crime Scenario Modelling

Burkhard Schafer, Jeroen Keppens

Research output: Contribution to journalArticlepeer-review


A crucial concern in the evaluation of evidence related to a major crime is the formulation of sufficient alternative plausible scenarios that can explain the available evidence. However, software aimed at assisting human crime investigators by automatically constructing crime scenarios from evidence is difficult to develop because of the almost infinite variation of plausible crime scenarios. This paper introduces a novel knowledge driven methodology for crime scenario construction and it presents a decision support system based on it. The approach works by storing the component events of the scenarios instead of entire scenarios and by providing an algorithm that can instantiate and compose these component events into useful scenarios. The scenario composition approach is highly adaptable to unanticipated cases because it allows component events to match the case under investigation in many different ways. Given a description of the available evidence, it generates a network of plausible scenarios that can then be analysed to devise effective evidence collection strategies. The applicability of the ideas presented here are demonstrated by means of a realistic example and prototype decision support software.
Original languageEnglish
Pages (from-to)203-22
Number of pages19
JournalExpert Systems with Applications
Issue number2
Publication statusPublished - 2006


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  • Assumption Based Peg Unification for Crime Scenario Modelling

    Schafer, B. & Keppens, J., 2005, Legal Knowledge and Information Systems - JURIX 2005: The Eighteenth Annual Conference on Legal Knowledge and Information Systems, Brussels, Belgium, 8-10 December 2005. Moens, M-F. & Spyns, P. (eds.). IOS Press, p. 49-58 (Frontiers in Artificial Intelligence and Applications; vol. 134).

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

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