Offender profiling for animal killing cases using Bayesian Networks

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  • ベイジアンネットワークによる動物殺害犯罪の犯人像推定
  • ベイジアンネットワーク ニ ヨル ドウブツ サツガイ ハンザイ ノ ハンニンゾウ スイテイ

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Abstract

The purpose of this study is to examine the validity of a Bayesian Network (BN) model of animal killing cases toward offender profiling. The BN model is a graphical model using a defined Directed Acyclic Graph and a probability definition such as conditional probability. In this study, first, BN models were automatically constructed on the basis of the training data. The constructed BN models mostly showed that the offenders’ age was related to the number of offenders and that the number of offenders was related to the type of animal victim (cat or the other animals except for cat and dog). Furthermore, the data suggest that cat victims were associated with parks as places of abandonment. Second, this study examined the accuracy of inferring an offenders’ age and the number of offenders by using a constructed BN model. The results of leave-one-out cross-validation showed that the precision rate for adults was 95.8％ and that for underage offenders was 80.0％. This study demonstrates the validity of offender profiling for animal killing cases.

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