The Legal Information Retrieval meets Artificial Intelligence (LI-RAI) workshop series aims to provide a venue hosting discussion of novel ideas, evaluations, and success stories concerning the application of Artificial Intelligence (AI) and Information Retrieval (IR) to the legal domain. All around the world, lawmakers, legal professionals, and citizens must cope with the sheer amount of legal knowledge present in legal documents. These documents can be norms, regulations, directives, legal cases, and other relevant material for legal practitioners, such as legal commentary. The continuous evolution of legal documents is a challenging setting, with implicit relationships playing an important role beyond explicit references. Recently, the adoption of shared machine-readable formats and FAIR principles, as well as methods and practices from the Semantic Web, have certainly improved the accessibility of legal knowledge and its interoperability. Still, retrieving legal knowledge and making sense of it are not solved problems. The legal community often has special requirements for retrieval systems (e.g., high recall, explainability). Artificial Intelligence (AI) is positioned as a lever to enhance our ability to find, understand, and correlate legal information, and to comprehend its relationship to reality, in terms of compliance evaluation and risk/benefit analysis. We call contributions on these topics in the form of papers, which will be collected in an open-access proceedings published on CEUR-WS.org and thus indexed by Scopus, DBLP, Google Scholar, and other citation databases.

De Luca, E.w., Fiorelli, M., Picca, D., Stellato, A., Wehnert, S. (2023). Legal Information Retrieval meets Artificial Intelligence (LIRAI). In HT '23: Proceedings of the 34th ACM Conference on Hypertext and Social Media (pp. 1-4). 1601 Broadway, 10th Floor, NEW YORK, NY, UNITED STATES : ASSOC COMPUTING MACHINERY [10.1145/3603163.3610575].

Legal Information Retrieval meets Artificial Intelligence (LIRAI)

Fiorelli M.;Stellato A.;
2023-01-01

Abstract

The Legal Information Retrieval meets Artificial Intelligence (LI-RAI) workshop series aims to provide a venue hosting discussion of novel ideas, evaluations, and success stories concerning the application of Artificial Intelligence (AI) and Information Retrieval (IR) to the legal domain. All around the world, lawmakers, legal professionals, and citizens must cope with the sheer amount of legal knowledge present in legal documents. These documents can be norms, regulations, directives, legal cases, and other relevant material for legal practitioners, such as legal commentary. The continuous evolution of legal documents is a challenging setting, with implicit relationships playing an important role beyond explicit references. Recently, the adoption of shared machine-readable formats and FAIR principles, as well as methods and practices from the Semantic Web, have certainly improved the accessibility of legal knowledge and its interoperability. Still, retrieving legal knowledge and making sense of it are not solved problems. The legal community often has special requirements for retrieval systems (e.g., high recall, explainability). Artificial Intelligence (AI) is positioned as a lever to enhance our ability to find, understand, and correlate legal information, and to comprehend its relationship to reality, in terms of compliance evaluation and risk/benefit analysis. We call contributions on these topics in the form of papers, which will be collected in an open-access proceedings published on CEUR-WS.org and thus indexed by Scopus, DBLP, Google Scholar, and other citation databases.
2023
Settore ING-INF/05
Settore INF/01
English
Rilevanza internazionale
Prefazione
Legal Informatics; Legal Information Retrieval; Legal Knowledge Representation; Legal Text Mining; Legal Compliance; FAIRness; Semantic Web; Linguistic Legal Linked Open Data; Explainable AI; High-Recall Retrieval
De Luca, E.w., Fiorelli, M., Picca, D., Stellato, A., Wehnert, S. (2023). Legal Information Retrieval meets Artificial Intelligence (LIRAI). In HT '23: Proceedings of the 34th ACM Conference on Hypertext and Social Media (pp. 1-4). 1601 Broadway, 10th Floor, NEW YORK, NY, UNITED STATES : ASSOC COMPUTING MACHINERY [10.1145/3603163.3610575].
De Luca, Ew; Fiorelli, M; Picca, D; Stellato, A; Wehnert, S
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2108/356526
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