A Bayesian network approach to the database serch problem in criminal proceedings

Détails

ID Serval
serval:BIB_3A968943B494
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Institution
Titre
A Bayesian network approach to the database serch problem in criminal proceedings
Périodique
Investigative Genetics
Auteur⸱e⸱s
Biedermann A., Vuille J., Taroni F.
ISSN
2041-2223
ISSN-L
2041-2223
Statut éditorial
Publié
Date de publication
08/2012
Peer-reviewed
Oui
Volume
3
Numéro
16
Pages
1-17
Langue
anglais
Résumé
Background
The 'database search problem', that is, the strengthening of a case - in terms of probative value - against an individual who is found as a result of a database search, has been approached during the last two decades with substantial mathematical analyses, accompanied by lively debate and centrally opposing conclusions. This represents a challenging obstacle in teaching but also hinders a balanced and coherent discussion of the topic within the wider scientific and legal community. This paper revisits and tracks the associated mathematical analyses in terms of Bayesian networks. Their derivation and discussion for capturing probabilistic arguments that explain the database search problem are outlined in detail. The resulting Bayesian networks offer a distinct view on the main debated issues, along with further clarity.
Methods
As a general framework for representing and analyzing formal arguments in probabilistic reasoning about uncertain target propositions (that is, whether or not a given individual is the source of a crime stain), this paper relies on graphical probability models, in particular, Bayesian networks. This graphical probability modeling approach is used to capture, within a single model, a series of key variables, such as the number of individuals in a database, the size of the population of potential crime stain sources, and the rarity of the corresponding analytical characteristics in a relevant population.
Results
This paper demonstrates the feasibility of deriving Bayesian network structures for analyzing, representing, and tracking the database search problem. The output of the proposed models can be shown to agree with existing but exclusively formulaic approaches.
Conclusions
The proposed Bayesian networks allow one to capture and analyze the currently most well-supported but reputedly counter-intuitive and difficult solution to the database search problem in a way that goes beyond the traditional, purely formulaic expressions. The method's graphical environment, along with its computational and probabilistic architectures, represents a rich package that offers analysts and discussants with additional modes of interaction, concise representation, and coherent communication.
Mots-clé
Database search, Evidential value, Bayesian approach, Bayesian networks
Création de la notice
08/01/2013 13:41
Dernière modification de la notice
20/08/2019 13:30
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