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.

Legal Information Retrieval systems: State-of-the-art and open issues / Sansone, Carlo; Sperlí, Giancarlo. - In: INFORMATION SYSTEMS. - ISSN 0306-4379. - 106:May(2022), pp. 1-14. [10.1016/j.is.2021.101967]

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

Sansone, Carlo;Sperlí, Giancarlo
2022

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.
2022
Legal Information Retrieval systems: State-of-the-art and open issues / Sansone, Carlo; Sperlí, Giancarlo. - In: INFORMATION SYSTEMS. - ISSN 0306-4379. - 106:May(2022), pp. 1-14. [10.1016/j.is.2021.101967]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/863939
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