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Legal Information Retrieval System with Entity-Based Query Expansion: Case study in Traffic Accident Litigation
DOI:
https://doi.org/10.24215/16666038.22.e12Keywords:
Information retrieval, relevance feedback, query expansion, legal knowledge baseAbstract
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.
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Published
2022-10-17
How to Cite
Gimenez Catacora, J. A., Casali, A., & Deco, C. (2022). Legal Information Retrieval System with Entity-Based Query Expansion: Case study in Traffic Accident Litigation. Journal of Computer Science and Technology, 22(2), e12. https://doi.org/10.24215/16666038.22.e12
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Copyright (c) 2022 Joel Arnaldo Gimenez Catacora, Ana Casali, Claudia Deco
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
