In this paper, we present a knowledge-based approach for legal document retrieval based on the organization of a textual data repository and on document embedding models. Pre-processed and embedded documents are iteratively classified at sentence level through a terminology extraction and concept formation cycle, using a zero-knowledge approach that offers a high degree of flexibility with regard to the integration of external knowledge and the variability of inputs, suitable to face the scarcity of annotated data and the specificity of terminology that feature the Italian legal domain document corpora.

Knowledge-Based Legal Document Retrieval: A Case Study on Italian Civil Court Decisions / V. Bellandi, S. Castano, P. Ceravolo, E. Damiani, A. Ferrara, S. Montanelli, S. Picascia, A. Polimeno, D. Riva (CEUR WORKSHOP PROCEEDINGS). - In: EKAW-C 2022 : EKAW 2022 Companion Volume / [a cura di] D. Symeonidou, R. Yu, D. Ceolin, M. Poveda-Villalón, D. Audrito, L. Di Caro, F. Grasso, R. Nai, E. Sulis, F.J. Ekaputra, O. Kutz, N. Troquard. - [s.l] : CEUR-WS, 2022. - pp. 1-13 (( Intervento presentato al 23. convegno International Conference on Knowledge Engineering and Knowledge Management, EKAW-C 2022 tenutosi a Bolzano nel 2022.

Knowledge-Based Legal Document Retrieval: A Case Study on Italian Civil Court Decisions

V. Bellandi
Primo
;
S. Castano
Secondo
;
P. Ceravolo;E. Damiani;A. Ferrara;S. Montanelli;S. Picascia;A. Polimeno
Penultimo
;
D. Riva
Ultimo
2022

Abstract

In this paper, we present a knowledge-based approach for legal document retrieval based on the organization of a textual data repository and on document embedding models. Pre-processed and embedded documents are iteratively classified at sentence level through a terminology extraction and concept formation cycle, using a zero-knowledge approach that offers a high degree of flexibility with regard to the integration of external knowledge and the variability of inputs, suitable to face the scarcity of annotated data and the specificity of terminology that feature the Italian legal domain document corpora.
legal document retrieval; legal knowledge extraction; semantic search; zero-shot learning
Settore INF/01 - Informatica
Artificial Intelligence Journal
Free University of Bozen-Bolzano
Universidad Politecnica de Madrid
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/949899
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