The paper focuses on the automatic extraction of domain knowledge from Italian legal texts and presents a fully-implemented ontology learning system (T2K, Text-2-Knowledge) that includes a battery of tools for Natural Language Processing, statistical text analysis and machine learning. Evaluated results show the considerable potential of systems like T2K, exploiting an incremental interleaving of NLP and machine learning techniques for accurate large-scale semi-automatic extraction and structuring of domain-specific knowledge.
Dal testo alla conoscenza e ritorno: estrazione terminologica e annotazione semantica di basi documentali di dominio
Dell'Orletta F;Marchi S;Montemagni S;Pirrelli V;Venturi G
2008
Abstract
The paper focuses on the automatic extraction of domain knowledge from Italian legal texts and presents a fully-implemented ontology learning system (T2K, Text-2-Knowledge) that includes a battery of tools for Natural Language Processing, statistical text analysis and machine learning. Evaluated results show the considerable potential of systems like T2K, exploiting an incremental interleaving of NLP and machine learning techniques for accurate large-scale semi-automatic extraction and structuring of domain-specific knowledge.| Campo DC | Valore | Lingua |
|---|---|---|
| dc.authority.ancejournal | AIDA INFORMAZIONI (ONLINE) | - |
| dc.authority.orgunit | Istituto di linguistica computazionale "Antonio Zampolli" - ILC | - |
| dc.authority.people | Dell'Orletta F | it |
| dc.authority.people | Lenci A | it |
| dc.authority.people | Marchi S | it |
| dc.authority.people | Montemagni S | it |
| dc.authority.people | Pirrelli V | it |
| dc.authority.people | Venturi G | it |
| dc.collection.id.s | b3f88f24-048a-4e43-8ab1-6697b90e068e | * |
| dc.collection.name | 01.01 Articolo in rivista | * |
| dc.contributor.appartenenza | Istituto di linguistica computazionale "Antonio Zampolli" - ILC | * |
| dc.contributor.appartenenza.mi | 918 | * |
| dc.date.accessioned | 2024/02/19 00:49:29 | - |
| dc.date.available | 2024/02/19 00:49:29 | - |
| dc.date.issued | 2008 | - |
| dc.description.abstracteng | The paper focuses on the automatic extraction of domain knowledge from Italian legal texts and presents a fully-implemented ontology learning system (T2K, Text-2-Knowledge) that includes a battery of tools for Natural Language Processing, statistical text analysis and machine learning. Evaluated results show the considerable potential of systems like T2K, exploiting an incremental interleaving of NLP and machine learning techniques for accurate large-scale semi-automatic extraction and structuring of domain-specific knowledge. | - |
| dc.description.affiliations | Università di Pisa; ILC-CNR | - |
| dc.description.allpeople | Dell'Orletta F.; Lenci A.; Marchi S.; Montemagni S.; Pirrelli V.; Venturi G. | - |
| dc.description.allpeopleoriginal | Dell'Orletta F.; Lenci A.; Marchi S.; Montemagni S.; Pirrelli V.; Venturi G. | - |
| dc.description.fulltext | none | en |
| dc.description.numberofauthors | 4 | - |
| dc.identifier.uri | https://hdl.handle.net/20.500.14243/37713 | - |
| dc.language.iso | ita | - |
| dc.miur.last.status.update | 2024-10-10T13:46:35Z | * |
| dc.relation.firstpage | 197 | - |
| dc.relation.issue | 1-2 | - |
| dc.relation.lastpage | 218 | - |
| dc.relation.numberofpages | 22 | - |
| dc.relation.volume | 26 | - |
| dc.subject.keywords | Natural Language Processing | - |
| dc.subject.keywords | Machine Learning | - |
| dc.subject.keywords | Knowledge extraction from texts | - |
| dc.subject.keywords | Ontology learning | - |
| dc.subject.keywords | Legal ontologies | - |
| dc.subject.singlekeyword | Natural Language Processing | * |
| dc.subject.singlekeyword | Machine Learning | * |
| dc.subject.singlekeyword | Knowledge extraction from texts | * |
| dc.subject.singlekeyword | Ontology learning | * |
| dc.subject.singlekeyword | Legal ontologies | * |
| dc.title | Dal testo alla conoscenza e ritorno: estrazione terminologica e annotazione semantica di basi documentali di dominio | en |
| dc.type.driver | info:eu-repo/semantics/article | - |
| dc.type.full | 01 Contributo su Rivista::01.01 Articolo in rivista | it |
| dc.type.miur | 262 | - |
| dc.type.referee | Sì, ma tipo non specificato | - |
| dc.ugov.descaux1 | 64541 | - |
| iris.orcid.lastModifiedDate | 2024/03/02 03:11:11 | * |
| iris.orcid.lastModifiedMillisecond | 1709345471314 | * |
| iris.sitodocente.maxattempts | 1 | - |
| Appare nelle tipologie: | 01.01 Articolo in rivista | |
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