Large-scale Legal Reasoning with Rules and Databases
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Baryannis, George
Batsakis, Sotiris
Tachmazidis, Ilias
Governatori, Guido
Islam, Mohammad Badiul
Liu, Qing
Robaldo, Livio
Siragusa, Giovanni
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Abstract
Traditionally, computational knowledge representation and reasoning focused its attention on rich domains such as the law. The main underlying assumption of traditional legal knowledge representation and reasoning is that knowledge and data are both available in main memory. However, in the era of big data, where large amounts of data are generated daily, an increasing range of scientific disciplines, as well as business and human activities, are becoming data-driven. This chapter summarises existing research on legal representation and reasoning in order to uncover technical challenges associated both with the integration of rules and databases and with the main concepts of the big data landscape. We expect these challenges lead naturally to future research directions towards achieving large scale legal reasoning with rules and databases.
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Journal of Applied Logics- IfCoLog Journal of Logics and their Applications
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8
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4
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© The Individual authors and College Publications 2021. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International (CC BY-NC-ND 4.0) License, which permits unrestricted, non-commercial use, distribution and reproduction in any medium, providing that the work is properly cited.
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Subject
Law and legal studies
Legal theory, jurisprudence and legal interpretation
Information systems
Science & Technology
Logic
Science & Technology - Other Topics
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Antoniou, G; Baryannis, G; Batsakis, S; Tachmazidis, I; Governatori, G; Islam, MB; Liu, Q; Robaldo, L; Siragusa, G, Large-scale Legal Reasoning with Rules and Databases, Journal of Applied Logics- IfCoLog Journal of Logics and their Applications, 2021, 8 (4), pp. 911-939