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Large-Scale Legal Reasoning with Rules and Databases

Livio Robaldo Orcid Logo, Grigoris Antoniou, George Baryannis, Sotiris Batsakis, Guido Governatori, Mohammad Badiul Islam, Qing Liu, Giovanni Siragusa, Ilias Tachmazidis

Journal of Applied Logics, Volume: 8, Issue: 4, Pages: 911 - 939

Swansea University Author: Livio Robaldo Orcid Logo

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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 b...

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Published in: Journal of Applied Logics
ISSN: 2631-9810 2631-9829
Published: College Publication 2021
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URI: https://cronfa.swan.ac.uk/Record/cronfa56725
first_indexed 2021-04-23T13:44:15Z
last_indexed 2021-08-12T03:13:51Z
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spelling 2021-08-11T12:30:37.4316500 v2 56725 2021-04-23 Large-Scale Legal Reasoning with Rules and Databases b711cf9f3a7821ec52bd1e53b4f6cf9e 0000-0003-4713-8990 Livio Robaldo Livio Robaldo true false 2021-04-23 HRCL 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 rangeof 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. Journal Article Journal of Applied Logics 8 4 911 939 College Publication 2631-9810 2631-9829 1 5 2021 2021-05-01 https://www.collegepublications.co.uk/ifcolog/?00046 COLLEGE NANME Hillary Rodham Clinton Law School COLLEGE CODE HRCL Swansea University 2021-08-11T12:30:37.4316500 2021-04-23T14:37:23.5849174 Faculty of Humanities and Social Sciences Hilary Rodham Clinton School of Law Livio Robaldo 0000-0003-4713-8990 1 Grigoris Antoniou 2 George Baryannis 3 Sotiris Batsakis 4 Guido Governatori 5 Mohammad Badiul Islam 6 Qing Liu 7 Giovanni Siragusa 8 Ilias Tachmazidis 9 56725__19978__eac2f3a4970841eb9e4d71f9d42c9394.pdf 56725.pdf 2021-05-24T13:11:25.6384087 Output 1353630 application/pdf Version of Record true true eng
title Large-Scale Legal Reasoning with Rules and Databases
spellingShingle Large-Scale Legal Reasoning with Rules and Databases
Livio Robaldo
title_short Large-Scale Legal Reasoning with Rules and Databases
title_full Large-Scale Legal Reasoning with Rules and Databases
title_fullStr Large-Scale Legal Reasoning with Rules and Databases
title_full_unstemmed Large-Scale Legal Reasoning with Rules and Databases
title_sort Large-Scale Legal Reasoning with Rules and Databases
author_id_str_mv b711cf9f3a7821ec52bd1e53b4f6cf9e
author_id_fullname_str_mv b711cf9f3a7821ec52bd1e53b4f6cf9e_***_Livio Robaldo
author Livio Robaldo
author2 Livio Robaldo
Grigoris Antoniou
George Baryannis
Sotiris Batsakis
Guido Governatori
Mohammad Badiul Islam
Qing Liu
Giovanni Siragusa
Ilias Tachmazidis
format Journal article
container_title Journal of Applied Logics
container_volume 8
container_issue 4
container_start_page 911
publishDate 2021
institution Swansea University
issn 2631-9810
2631-9829
publisher College Publication
college_str Faculty of Humanities and Social Sciences
hierarchytype
hierarchy_top_id facultyofhumanitiesandsocialsciences
hierarchy_top_title Faculty of Humanities and Social Sciences
hierarchy_parent_id facultyofhumanitiesandsocialsciences
hierarchy_parent_title Faculty of Humanities and Social Sciences
department_str Hilary Rodham Clinton School of Law{{{_:::_}}}Faculty of Humanities and Social Sciences{{{_:::_}}}Hilary Rodham Clinton School of Law
url https://www.collegepublications.co.uk/ifcolog/?00046
document_store_str 1
active_str 0
description 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 rangeof 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.
published_date 2021-05-01T14:09:25Z
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score 11.048194

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