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.
Palmirani Monica, Bincoletto Giorgia, Leone Valentina, Sapienza Salvatore, Sovrano Francesco (2019). PrOnto Ontology Refinement Through Open Knowledge Extraction. Amsterdam : IOS Press [10.3233/FAIA190326].
PrOnto Ontology Refinement Through Open Knowledge Extraction
Palmirani Monica;Bincoletto Giorgia;Leone Valentina;Sapienza Salvatore;Sovrano Francesco
2019
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 | |
|---|---|---|---|
|
FAIA-322-FAIA190326.pdf
accesso aperto
Tipo:
Versione (PDF) editoriale
Licenza:
Licenza per Accesso Aperto. Creative Commons Attribuzione - Non commerciale (CCBYNC)
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.
