research-article

Legal Information Retrieval systems: : State-of-the-art and open issues

Authors:

Giancarlo SperlíAuthors Info & Claims

Volume 106, Issue C

https://doi.org/10.1016/j.is.2021.101967

Published: 01 May 2022 Publication History

Abstract

In the last years, the legal domain has been revolutionized by the use of Information and Communication Technologies, producing large amount of digital information. Legal practitioners’ needs, then, in browsing these repositories has required to investigate more efficient retrieval methods, that assume more relevance because digital information is mostly unstructured. In this paper we analyze the state-of-the-art of artificial intelligence approaches for legal domain, focusing on Legal Information Retrieval systems based on Natural Language Processing, Machine Learning and Knowledge Extraction techniques. Finally, we also discuss challenges – mainly focusing on retrieving similar cases, statutes or paragraph for supporting latest cases’ analysis – and open issues about Legal Information Retrieval systems.

Highlights

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Legal Information Retrieval aims to model information search from legal practitioners.

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LIR is an IR task to identify most suitable information w.r.t the input query.

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LIR systems can be classified in NLP, Deep Learning and Ontology based techniques.

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Several challenges are arising for Legal Information Extraction and Entailment.

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Cited By

Colombo ASerra ESpezzano F(2024)Leveraging Knowledge Graphs and LLMs to Support and Monitor Legislative SystemsProceedings of the 33rd ACM International Conference on Information and Knowledge Management10.1145/3627673.3680268(5443-5446)Online publication date: 21-Oct-2024
https://dl.acm.org/doi/10.1145/3627673.3680268
Xie NBai YGao HXue ZFang FZhao QLi ZZhu LNi SYang MSerra ESpezzano F(2024)DeliLaw: A Chinese Legal Counselling System Based on a Large Language ModelProceedings of the 33rd ACM International Conference on Information and Knowledge Management10.1145/3627673.3679219(5299-5303)Online publication date: 21-Oct-2024
https://dl.acm.org/doi/10.1145/3627673.3679219
Greco CTagarelli A(2024)Bringing order into the realm of Transformer-based language models for artificial intelligence and lawArtificial Intelligence and Law10.1007/s10506-023-09374-732:4(863-1010)Online publication date: 1-Dec-2024
https://dl.acm.org/doi/10.1007/s10506-023-09374-7
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Legal Information Retrieval systems: State-of-the-art and open issues

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Information & Contributors

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Published In

cover image Information Systems

Information Systems Volume 106, Issue C

May 2022

210 pages

ISSN:0306-4379

Issue’s Table of Contents

Elsevier Ltd.

Publisher

Elsevier Science Ltd.

United Kingdom

Publication History

Published: 01 May 2022

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Cited By

Colombo ASerra ESpezzano F(2024)Leveraging Knowledge Graphs and LLMs to Support and Monitor Legislative SystemsProceedings of the 33rd ACM International Conference on Information and Knowledge Management10.1145/3627673.3680268(5443-5446)Online publication date: 21-Oct-2024
https://dl.acm.org/doi/10.1145/3627673.3680268
Xie NBai YGao HXue ZFang FZhao QLi ZZhu LNi SYang MSerra ESpezzano F(2024)DeliLaw: A Chinese Legal Counselling System Based on a Large Language ModelProceedings of the 33rd ACM International Conference on Information and Knowledge Management10.1145/3627673.3679219(5299-5303)Online publication date: 21-Oct-2024
https://dl.acm.org/doi/10.1145/3627673.3679219
Greco CTagarelli A(2024)Bringing order into the realm of Transformer-based language models for artificial intelligence and lawArtificial Intelligence and Law10.1007/s10506-023-09374-732:4(863-1010)Online publication date: 1-Dec-2024
https://dl.acm.org/doi/10.1007/s10506-023-09374-7
Zadgaonkar AAgrawal A(2024)An Approach for Analyzing Unstructured Text Data Using Topic Modeling Techniques for Efficient Information ExtractionNew Generation Computing10.1007/s00354-023-00230-542:1(109-134)Online publication date: 1-Mar-2024
https://dl.acm.org/doi/10.1007/s00354-023-00230-5
Smywiński-Pohl ALibal T(2024)Enhancing Legal Argument Retrieval with Optimized Language Model TechniquesNew Frontiers in Artificial Intelligence10.1007/978-981-97-3076-6_7(93-108)Online publication date: 28-May-2024
https://dl.acm.org/doi/10.1007/978-981-97-3076-6_7
Abro WKteich HBouraoui Z(2024)Self-supervised Segment Contrastive Learning for Medical Document RepresentationArtificial Intelligence in Medicine10.1007/978-3-031-66538-7_31(312-321)Online publication date: 9-Jul-2024
https://dl.acm.org/doi/10.1007/978-3-031-66538-7_31
Landoni MHuibers TMurgia EPera M(2024)Good for Children, Good for All?Advances in Information Retrieval10.1007/978-3-031-56066-8_24(302-313)Online publication date: 24-Mar-2024
https://dl.acm.org/doi/10.1007/978-3-031-56066-8_24
Nowrozy RAhmed K(2023)Enhancing Health Information Systems Security: An Ontology Model ApproachHealth Information Science10.1007/978-981-99-7108-4_8(91-100)Online publication date: 23-Oct-2023
https://dl.acm.org/doi/10.1007/978-981-99-7108-4_8

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