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Legal Information Retrieval System with Entity-Based Query Expansion: Case study in Traffic Accident Litigation

Authors :
Joel Arnaldo Gimenez Catacora
Ana Casali
Claudia Deco
Source :
Journal of Computer Science and Technology, Vol 22, Iss 2, Pp e12-e12 (2022)
Publication Year :
2022
Publisher :
Postgraduate Office, School of Computer Science, Universidad Nacional de La Plata, 2022.

Abstract

This article describes an information retrieval system with entity query expansion by relevance feedback. The performance of the system is tested assuming its usage as a support tool for lawyers constructing a legal framework for a case. The objective is to improve the precision of results when searching for relevant jurisprudence. For this, the entities belonging to a knowledge base are used as a means to expand the query. The expansion can be done using either an automatic or an interactive mechanism. This second approach suggests to the user concepts related to the query, which might improve the search experience. An ontology and a knowledge base, called LegalOnto and LegalBase, respectively, were developed. The ontology includes concepts not addressed by existing legal ontologies, and the knowledge base integrates LegalOnto with the thesaurus of the Argentine System of Legal Information (Sistema Argentino de Informacion ´ Jur´ıdica: SAIJ), enriched in the subject of traffic accidents. Quantitative experimentation is carried out upon a set of court documents that are used to populate the knowledge base. Preliminary results are encouraging.

Details

Language :
English
ISSN :
16666046 and 16666038
Volume :
22
Issue :
2
Database :
Directory of Open Access Journals
Journal :
Journal of Computer Science and Technology
Publication Type :
Academic Journal
Accession number :
edsdoj.99cca13f6502472aadf3ad7dd4c61a52
Document Type :
article
Full Text :
https://doi.org/10.24215/16666038.22.e12