Abstract

This paper presents a methodology for helping citizens obtain guidance and training when submitting a natural language description of a legal case they are interested in. This is done via an automatic mechanism, which firstly extracts relevant legal concepts from the given textual description, by relying upon an underlying legal ontology built for such a purpose and an enrichment process based on common-sense knowledge. Then, it proceeds to generate a training path meant to provide citizens with a better understanding of the legal issues arising from the given case, with corresponding links to relevant laws and jurisprudence retrieved from an external legal repository. This work de-scribes the creation of the underlying legal ontology from existing sources and the ontology integration algorithm used for its production; besides, it details the generation of the training paths and reports the results of the preliminary experimentation that has been carried out so far. This methodology has been implemented in an Online Dispute Resolution (ODR) system that is part of an Italian initiative for assisted legal mediation.

Citation

Capuano, N., Longhi, A., Salerno, S. & Toti, D. (2015). Ontology-driven Generation of Training Paths in the Legal Domain. International Journal of Emerging Technologies in Learning (iJET), 10(7), 14-22. Kassel, Germany: International Journal of Emerging Technology in Learning. Retrieved August 7, 2024 from https://www.learntechlib.org/p/151171/.

Keywords

• adaptive learning systems
• Knowledge Representation
• Legal Issues
• online dispute resolution
• ontology engineering
• ontology integration
• semantic search
• text analysis
• Training