Ontology-driven Generation of Training Paths in the Legal Domain

Nicola Capuano, Andrea Longhi, Saverio Salerno, Daniele Toti


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.


adaptive learning systems; semantic search; online dispute resolution; text analysis; knowledge representation; ontology engineering; ontology integration

Full Text:


Copyright (c) 2017 Nicola Capuano, Andrea Longhi, Saverio Salerno, Daniele Toti

International Journal of Emerging Technologies in Learning. ISSN: 1863-0383
Creative Commons License SPARC Europe Seal
Web of Science ESCI logo Engineering Information logo INSPEC logo DBLP logo ELSEVIER Scopus logo EDiTLib logo EBSCO logo Ulrich's logo Google Scholar logo Microsoft® Academic SearchDOAJ logo