Predicting Reasoner Performance on ABox Intensive OWL 2 EL Ontologies

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.

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Year of publication:	2018
Authors:	Li, Yuan-Fang ; Pan, Jeff Z. ; Bobed, Carlos ; Guclu, Isa ; Bobillo, Fernando ; Kollingbaum, Martin J. ; Mena, Eduardo
Published in:	International Journal on Semantic Web and Information Systems (IJSWIS). - IGI Global, ISSN 1552-6291, ZDB-ID 2401011-X. - Vol. 14.2018, 1 (01.01.), p. 1-30
Publisher:	IGI Global
Subject:	ABox Reasoning \| Machine Learning \| Ontology \| Performance Prediction \| Semantic Web

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Type of publication:	Article
Language:	English
Other identifiers:	10.4018/IJSWIS.2018010101 [DOI]
Source:	Other ZBW resources

Persistent link: https://www.econbiz.de/10012048279