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

Valerio Bellandi, Silvana Castano, Paolo Ceravolo, Ernesto Damiani, Alfio Ferrara, Stefano Montanelli, Sergio Picascia, Antongiacomo Polimeno, Davide Riva

Research output: Contribution to journalConference articlepeer-review

2 Scopus citations

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.

Original languageBritish English
JournalCEUR Workshop Proceedings
Volume3256
StatePublished - 2022
Event23rd International Conference on Knowledge Engineering and Knowledge Management, EKAW-C 2022 - Bozen-Bolzano, Italy
Duration: 26 Sep 202229 Sep 2022

Keywords

  • legal document retrieval
  • legal knowledge extraction
  • semantic search
  • zero-shot learning

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