extended-abstract

Transfer of predictive models for classification of statutory texts in multi-jurisdictional settings

Authors:

Jaromír Šavelka,

Kevin D. AshleyAuthors Info & Claims

ICAIL '15: Proceedings of the 15th International Conference on Artificial Intelligence and Law

Pages 216 - 220

https://doi.org/10.1145/2746090.2746109

Published: 08 June 2015 Publication History

Abstract

In this paper we use statistical machine learning to classify statutory texts in terms of highly specific functional categories. We focus on regulatory provisions from multiple US state jurisdictions, all dealing with the same general topic of public health system emergency preparedness and response. In prior work we have established that one can improve classification performance on one jurisdiction's statutory texts using texts from another jurisdiction. Here we describe a framework facilitating transfer of predictive models for classification of statutory texts among multiple state jurisdictions. Our results show that the classification performance improves as we employ an increasing number of models trained on data coming from different states.

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Cited By

Savelka JAndrade FGrabmair M(2023)Unlocking Practical Applications in Legal DomainProceedings of the Nineteenth International Conference on Artificial Intelligence and Law10.1145/3594536.3595161(447-451)Online publication date: 19-Jun-2023
https://dl.acm.org/doi/10.1145/3594536.3595161
Metsker OTrofimov EKopanitsa G(2021)Application of Machine Learning Metrics for Dynamic E-justice Processes2021 28th Conference of Open Innovations Association (FRUCT)10.23919/FRUCT50888.2021.9347598(293-300)Online publication date: 27-Jan-2021
https://doi.org/10.23919/FRUCT50888.2021.9347598
Savelka JWestermann HBenyekhlef KAlexander CGrant JAmariles DHamdani RMeeùs STroussel AAraszkiewicz MAshley KAshley ABranting KFalduti MGrabmair MHarašta JNovotná TTippett EJohnson SMaranhão JWyner A(2021)Lex RosettaProceedings of the Eighteenth International Conference on Artificial Intelligence and Law10.1145/3462757.3466149(129-138)Online publication date: 21-Jun-2021
https://dl.acm.org/doi/10.1145/3462757.3466149
Show More Cited By

Index Terms

Transfer of predictive models for classification of statutory texts in multi-jurisdictional settings
1. Applied computing
  1. Document management and text processing
2. Information systems
  1. Information retrieval
    1. Retrieval models and ranking

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cover image ACM Other conferences

ICAIL '15: Proceedings of the 15th International Conference on Artificial Intelligence and Law

June 2015

246 pages

ISBN:9781450335225

DOI:10.1145/2746090

Conference Chair:
Ted Sichelman
University of San Diego School of Law, San Diego, CA
,
Program Chair:
Katie Atkinson
University of Liverpool, Liverpool, UK

Copyright © 2015 Owner/Author.

Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

Sponsors

Center for IP Law & Markets: Center for Intellectual Property Law & Markets, University of San Diego School of Law
TrademarkNow: TrademarkNow
The International Association for Artificial Intelligence and Law
Davis Polk: Davis Polk & Wardwell LLP
Legal Robot: Legal Robot
Thomson Reuters: Thomson Reuters Corporation

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SIGAI: ACM Special Interest Group on Artificial Intelligence

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 08 June 2015

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Extended-abstract

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ICAIL '15

Sponsor:

Center for IP Law & Markets
TrademarkNow
Davis Polk
Legal Robot
Thomson Reuters

ICAIL '15: 15th International Conference on Artificial Intelligence and Law

June 8 - 12, 2015

California, San Diego

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ICAIL '15 Paper Acceptance Rate 30 of 58 submissions, 52%;

Overall Acceptance Rate 69 of 169 submissions, 41%

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Cited By

Savelka JAndrade FGrabmair M(2023)Unlocking Practical Applications in Legal DomainProceedings of the Nineteenth International Conference on Artificial Intelligence and Law10.1145/3594536.3595161(447-451)Online publication date: 19-Jun-2023
https://dl.acm.org/doi/10.1145/3594536.3595161
Metsker OTrofimov EKopanitsa G(2021)Application of Machine Learning Metrics for Dynamic E-justice Processes2021 28th Conference of Open Innovations Association (FRUCT)10.23919/FRUCT50888.2021.9347598(293-300)Online publication date: 27-Jan-2021
https://doi.org/10.23919/FRUCT50888.2021.9347598
Savelka JWestermann HBenyekhlef KAlexander CGrant JAmariles DHamdani RMeeùs STroussel AAraszkiewicz MAshley KAshley ABranting KFalduti MGrabmair MHarašta JNovotná TTippett EJohnson SMaranhão JWyner A(2021)Lex RosettaProceedings of the Eighteenth International Conference on Artificial Intelligence and Law10.1145/3462757.3466149(129-138)Online publication date: 21-Jun-2021
https://dl.acm.org/doi/10.1145/3462757.3466149
Walker VHan JNi XYoseda KKeppens JGovernatori G(2017)Semantic types for computational legal reasoningProceedings of the 16th edition of the International Conference on Articial Intelligence and Law10.1145/3086512.3086535(217-226)Online publication date: 12-Jun-2017
https://dl.acm.org/doi/10.1145/3086512.3086535

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