Paper Info
Title
Ontology learning from Italian legal texts
Abstract
The paper reports on the methodology and preliminary results of a case study in automatically extracting ontological knowledge from Italian legislative texts. We use a fully--implemented ontology learning system (T2K) that includes a battery of tools for Natural Language Processing (NLP), statistical text analysis and machine language learning. Tools are dynamically integrated to provide an incremental representation of the content of vast repositories of unstructured documents. Evaluated results, however preliminary, show the great potential of NLP--powered incremental systems like T2K for accurate large--scale semi--automatic extraction of legal ontologies.
Year
Venue
Keywords
2009
Law, Ontologies and the Semantic Web
machine language learning,italian legal text,incremental representation,italian legislative text,great potential,automatic extraction,preliminary result,incremental system,case study,natural language processing,evaluated result,document management
Field
DocType
Citations 
Ontology (information science),Ontology,Document management system,Computer science,Machine code,Information extraction,Artificial intelligence,Natural language processing,Upper ontology,Ontology learning
Conference
10
PageRank 
References 
Authors
0.81
10
4
Name
Order
Citations
PageRank
Alessandro Lenci163361.92
Simonetta Montemagni225533.40
Vito Pirrelli311822.64
Giulia Venturi413221.20