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, Monica; Bincoletto, Giorgia; Leone, Valentina; Sapienza, Salvatore; Sovrano, Francesco. - 322:(2019), pp. 205-210. ( 32nd International Conference on Legal Knowledge and Information Systems: JURIX 2019 Madrid 11th-13th December 2019) [10.3233/FAIA190326].
Pronto ontology refinement through open knowledge extraction
Bincoletto, GiorgiaSecondo
;
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 | |
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