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A Language Modelling approach to linking criminal styles with offender characteristics

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Title: A Language Modelling approach to linking criminal styles with offender characteristics
Authors: Bache, R.1 bache@dcs.gla.ac.uk, Crestani, F.2 fabio.crestani@unisi.ch, Canter, D.3, Youngs, D.3
Source: Data & Knowledge Engineering. Mar2010, Vol. 69 Issue 3, p303-315. 13p.
Subjects: Programming languages, MODEL (Computer program language), Criminals, Computer hackers, Bernoulli numbers, Information retrieval, QUERY (Information retrieval system)
Abstract: Abstract: The ability to infer the characteristics of offenders from their criminal behaviour (‘offender profiling’) has only been partially successful since it has relied on subjective judgments based on limited data. Words and structured data used in crime descriptions recorded by the police relate to behavioural features. Thus Language Modelling was applied to an existing police archive to link behavioural features with significant characteristics of offenders. Both multinomial and multiple Bernoulli models were used. Although categories selected are gender, age group, ethnic appearance and broad occupation (employed or not), in principle this can be applied to any characteristic recorded. Results indicate that statistically significant relationships exist between all characteristics for many types of crime. Bernoulli models tend to perform better than multinomial ones. It is also possible to identify automatically specific terms which when taken together give insight into the style of offending related to a particular group. [Copyright &y& Elsevier]
Copyright of Data & Knowledge Engineering is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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DbLabel: Engineering Source
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PubType: Academic Journal
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  Data: A Language Modelling approach to linking criminal styles with offender characteristics
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  Data: <searchLink fieldCode="AR" term="%22Bache%2C+R%2E%22">Bache, R.</searchLink><relatesTo>1</relatesTo><i> bache@dcs.gla.ac.uk</i><br /><searchLink fieldCode="AR" term="%22Crestani%2C+F%2E%22">Crestani, F.</searchLink><relatesTo>2</relatesTo><i> fabio.crestani@unisi.ch</i><br /><searchLink fieldCode="AR" term="%22Canter%2C+D%2E%22">Canter, D.</searchLink><relatesTo>3</relatesTo><br /><searchLink fieldCode="AR" term="%22Youngs%2C+D%2E%22">Youngs, D.</searchLink><relatesTo>3</relatesTo>
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  Data: <searchLink fieldCode="JN" term="%22Data+%26+Knowledge+Engineering%22">Data & Knowledge Engineering</searchLink>. Mar2010, Vol. 69 Issue 3, p303-315. 13p.
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  Data: <searchLink fieldCode="DE" term="%22Programming+languages%22">Programming languages</searchLink><br /><searchLink fieldCode="DE" term="%22MODEL+%28Computer+program+language%29%22">MODEL (Computer program language)</searchLink><br /><searchLink fieldCode="DE" term="%22Criminals%22">Criminals</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+hackers%22">Computer hackers</searchLink><br /><searchLink fieldCode="DE" term="%22Bernoulli+numbers%22">Bernoulli numbers</searchLink><br /><searchLink fieldCode="DE" term="%22Information+retrieval%22">Information retrieval</searchLink><br /><searchLink fieldCode="DE" term="%22QUERY+%28Information+retrieval+system%29%22">QUERY (Information retrieval system)</searchLink>
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  Data: Abstract: The ability to infer the characteristics of offenders from their criminal behaviour (‘offender profiling’) has only been partially successful since it has relied on subjective judgments based on limited data. Words and structured data used in crime descriptions recorded by the police relate to behavioural features. Thus Language Modelling was applied to an existing police archive to link behavioural features with significant characteristics of offenders. Both multinomial and multiple Bernoulli models were used. Although categories selected are gender, age group, ethnic appearance and broad occupation (employed or not), in principle this can be applied to any characteristic recorded. Results indicate that statistically significant relationships exist between all characteristics for many types of crime. Bernoulli models tend to perform better than multinomial ones. It is also possible to identify automatically specific terms which when taken together give insight into the style of offending related to a particular group. [Copyright &y& Elsevier]
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  Data: <i>Copyright of Data & Knowledge Engineering is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=47824107
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