Predicting reasoner performance on ABox intensive OWL 2 EL ontologies

Pan, Jeff Z. ; Bobed, Carlos ; Guclu, Isa ; Bobillo, Fernando (Universidad de Zaragoza) ; Kollingbaum, Martin J. ; Mena, Eduardo (Universidad de Zaragoza) ; Li, Yuan-Fang

Resumen: In this article, the authors introduce the notion of ABox intensity in the context of predicting reasoner performance to improve the representativeness of ontology metrics, and they develop new metrics that focus on ABox features of OWL 2 EL ontologies. Their experiments show that taking into account the intensity through the proposed metrics contributes to overall prediction accuracy for ABox intensive ontologies.

Idioma: Inglés

DOI: 10.4018/IJSWIS.2018010101

Año: 2018

Publicado en: International Journal on Semantic Web and Information Systems 14, 1 (2018), 1-30
ISSN: 1552-6283

Factor impacto JCR: 1.833 (2018)

Categ. JCR: COMPUTER SCIENCE, INFORMATION SYSTEMS rank: 91 / 155 = 0.587 (2018) - Q3 - T2
Categ. JCR: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE rank: 79 / 133 = 0.594 (2018) - Q3 - T2

Factor impacto SCIMAGO: 0.283 - Information Systems (Q3) - Computer Networks and Communications (Q3)

Financiación: info:eu-repo/grantAgreement/ES/DGA/FSE
Financiación: info:eu-repo/grantAgreement/EC/FP7/286348/EU/Knowledge Driven Data Exploitation/K-DRIVE
Financiación: info:eu-repo/grantAgreement/ES/MINECO/TIN2013-46238-C4-4-R
Financiación: info:eu-repo/grantAgreement/ES/MINECO/TIN2016-78011-C4-3-R

Tipo y forma: Article (PostPrint)

Área (Departamento): Área Lenguajes y Sistemas Inf. (Dpto. Informát.Ingenie.Sistms.)