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Crime Knowledge Extraction: an Ontology-driven Approach for Detecting Abstract Terms in Case Law Decisions

Authors:

Silvana Castano,

Alfio Ferrara,

Mattia Falduti,

Stefano MontanelliAuthors Info & Claims

ICAIL '19: Proceedings of the Seventeenth International Conference on Artificial Intelligence and Law

Pages 179 - 183

https://doi.org/10.1145/3322640.3326730

Published: 17 June 2019 Publication History

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Abstract

In this paper, we present CRIKE, a data-science approach to automatically detect concrete applications of legal abstract terms in case-law decisions. To this purpose, CRIKE relies on the use of the LATO ontology where legal abstract terms are properly formalized as concepts and relations among concepts. Using LATO, CRIKE aims at discovering how and where legal abstract terms are applied by judges in their legal argumentation. Moreover, we detect the terminology used in the text of case-law decisions to characterize concrete abstract-term instances. A case-study on a case-law decisions dataset provided by the Court of Milan, Italy, is also discussed.

References

[1]

Kevin D Ashley. 2017. Artificial Intelligence and Legal Analytics: New Tools for Law Practice in the Digital Age. Cambridge University Press.

Google Scholar

[2]

Enrico Francesconi, Simonetta Montemagni, Wim Peters, and Daniela Tiscornia. 2010. Integrating a BottomâĂŞUp and TopâĂŞDown Methodology for Building Semantic Resources for the Multilingual Legal Domain. Vol. 6036. Springer, 95--121.

Google Scholar

[3]

Anne Gardner. 1987. An Artificial Intelligence Approach to Legal Reasoning. MIT Press, Cambridge, MA, USA.

Digital Library

Google Scholar

[4]

Matthias Grabmair, Kevin D Ashley, Ran Chen, Preethi Sureshkumar, Chen Wang, Eric Nyberg, and Vern R Walker. 2015. Introducing LUIMA: an Experiment in Legal Conceptual Retrieval of Vaccine Injury Decisions Using a UIMA Type System and Tools. In Proc. of the 15th Int. Conference on Artificial Intelligence and Law. ACM, 69--78.

Digital Library

Google Scholar

[5]

Guiraude Lame. 2005. Using NLP Techniques to Identify Legal Ontology Components: Concepts and Relations. Springer Berlin Heidelberg, 169--184.

Digital Library

Google Scholar

[6]

Alessandro Lenci, Simonetta Montemagni, Vito Pirrelli, and Giulia Venturi. 2007. NLP-based Ontology Learning from Legal Texts. A Case Study. In Proc. of the 2nd Workshop on Legal Ontologies and Artificial Intelligence Techniques. Citeseer, 113--129.

Google Scholar

[7]

José Saias and Paulo Quaresma. 2005. A Methodology to Create Legal Ontologies in a Logic Programming Information Retrieval System. Springer, 185--200.

Google Scholar

[8]

Jaromir Savelka and Kevin D Ashley. 2016. Extracting Case Law Sentences for Argumentation about the Meaning of Statutory Terms. In Proc. of the 3rd Int. Workshop on Argument Mining. 50--59.

Crossref

Google Scholar

[9]

Jaromir Savelka, Matthias Grabmair, and Kevin D Ashley. 2014. Mining Information from Statutory Texts in Multi-Jurisdictional Settings. In Proc. of the Int. Conference on Legal Knowledge and Information Systems. IOS Press, 133--142.

Google Scholar

[10]

The European Monitoring Centre for Drugs and Drugs Addiction. 2018. Italy, Country Drug Report 2018. Technical Report. The European Monitoring Centre for Drugs and Drugs Addiction.

Google Scholar

[11]

Daniela Tiscornia. 2006. The LOIS project: Lexical Ontologies for Legal Information Sharing. In Proc. of the V Legislative XML Workshop. 189--204.

Google Scholar

[12]

PRS Visser and TJM Bench-Capon. 1996. The Formal Specification of a Legal Ontology. In Proc. of the Int. Conference on Legal Knowledge and Information Systems.

Google Scholar

Cited By

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Tuarob STatiyamaneekul PPongpaichet STawichsri TNoraset T(2025)Beyond administrative reports: a deep learning framework for classifying and monitoring crime and accidents leveraging large-scale online newsNeural Computing and Applications10.1007/s00521-024-10833-8Online publication date: 15-Feb-2025
https://doi.org/10.1007/s00521-024-10833-8
Falduti MGriffo C(2024)Ontological models for representing image-based sexual abusesComputer Law & Security Review10.1016/j.clsr.2024.10599954(105999)Online publication date: Sep-2024
https://doi.org/10.1016/j.clsr.2024.105999
Sansone CSperlí G(2022)Legal Information Retrieval systemsInformation Systems10.1016/j.is.2021.101967106:COnline publication date: 1-May-2022
https://dl.acm.org/doi/10.1016/j.is.2021.101967
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Index Terms

Crime Knowledge Extraction: an Ontology-driven Approach for Detecting Abstract Terms in Case Law Decisions
1. Information systems
  1. Information retrieval
    1. Document representation
      1. Ontologies

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ICAIL '19: Proceedings of the Seventeenth International Conference on Artificial Intelligence and Law

June 2019

312 pages

ISBN:9781450367547

DOI:10.1145/3322640

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Univ. of Montreal: University of Montreal
AAAI
IAAIL: Intl Asso for Artifical Intel & Law

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Published: 17 June 2019

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ICAIL '19: Seventeenth International Conference on Artificial Intelligence and Law

June 17 - 21, 2019

QC, Montreal, Canada

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Tuarob STatiyamaneekul PPongpaichet STawichsri TNoraset T(2025)Beyond administrative reports: a deep learning framework for classifying and monitoring crime and accidents leveraging large-scale online newsNeural Computing and Applications10.1007/s00521-024-10833-8Online publication date: 15-Feb-2025
https://doi.org/10.1007/s00521-024-10833-8
Falduti MGriffo C(2024)Ontological models for representing image-based sexual abusesComputer Law & Security Review10.1016/j.clsr.2024.10599954(105999)Online publication date: Sep-2024
https://doi.org/10.1016/j.clsr.2024.105999
Sansone CSperlí G(2022)Legal Information Retrieval systemsInformation Systems10.1016/j.is.2021.101967106:COnline publication date: 1-May-2022
https://dl.acm.org/doi/10.1016/j.is.2021.101967
Falduti MGriffo C(2022)Modeling Cybercrime with UFO: An Ontological Analysis of Non-Consensual Pornography CasesConceptual Modeling10.1007/978-3-031-17995-2_27(380-394)Online publication date: 10-Oct-2022
https://doi.org/10.1007/978-3-031-17995-2_27
Castano SFalduti MFerrara AMontanelli S(2021)A knowledge-centered framework for exploration and retrieval of legal documentsInformation Systems10.1016/j.is.2021.101842(101842)Online publication date: Jul-2021
https://doi.org/10.1016/j.is.2021.101842

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Modeling Cybercrime with UFO: An Ontological Analysis of Non-Consensual Pornography Cases

The Digital Crime Tsunami

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