This paper presents a refinement of PrOnto ontology using a validation test based on legal experts’ annotation of privacy policies combined with an Open Knowledge Extraction algorithm. Three iterations were performed, and a final test using new privacy policies. The results are 75% of detection of concepts and relationships in the policy texts and an increase of 29% in the accuracy using the new refined version of PrOnto enriched with SKOSXL lexicon terms and definitions.
Pronto ontology refinement through open knowledge extraction / Palmirani, M.; Bincoletto, G.; Leone, V.; Sapienza, S.; Sovrano, F.. - 322:(2019), pp. 205-210. (Intervento presentato al convegno 32nd International Conference on Legal Knowledge and Information Systems, JURIX 2019 tenutosi a Madrid nel 11-13 December 2019) [10.3233/FAIA190326].
Pronto ontology refinement through open knowledge extraction
Bincoletto G.;
2019-01-01
Abstract
This paper presents a refinement of PrOnto ontology using a validation test based on legal experts’ annotation of privacy policies combined with an Open Knowledge Extraction algorithm. Three iterations were performed, and a final test using new privacy policies. The results are 75% of detection of concepts and relationships in the policy texts and an increase of 29% in the accuracy using the new refined version of PrOnto enriched with SKOSXL lexicon terms and definitions.| File | Dimensione | Formato | |
|---|---|---|---|
|
Palmirani_Bincoletto_Leone_Sapienza_Sovrano_2019.pdf
accesso aperto
Tipologia:
Versione editoriale (Publisher’s layout)
Licenza:
Creative commons
Dimensione
328.62 kB
Formato
Adobe PDF
|
328.62 kB | Adobe PDF | Visualizza/Apri |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione
