, Table 5: Positive members of the detected " hard " axiom pairs
, SubClassOf(dbo:ArchitecturalStructure gml:_Feature)
Product dbo:MeanOfTransportation) SubClassOf(dbo:Eukaryote dbo:Animal) SubClassOf(dbo:Library gml:_Feature) SubClassOf(schema:School gml:_Feature) SubClassOf(dbo:Racecourse gml:_Feature) SubClassOf(dbo:WomensTennisAssociationTournament gml:_Feature) ,
, SubClassOf(schema:Airport gml:_Feature) SubClassOf(dbo:GovernmentAgency schema:GovernmentOrganization)
GovernmentAgency gml:_Feature) SubClassOf(dbo:Venue dbo:Building) SubClassOf(dbo:Venue dbo:Theatre) ,
Venue gml:_Feature) SubClassOf(dbo:YearInSpaceflight skos:Concept) SubClassOf(dbo:Village gml:_Feature) SubClassOf(dbo:ProtectedArea gml:_Feature) SubClassOf(dbo:ComedyGroup foaf:Person) REFERENCES [1] Bruno Apolloni Interpolating Support Information Granules, Neurocomputing, vol.71, pp.2433-2445, 2008. ,
, Granular Regression, pp.147-156, 2005.
Support vector clustering, Scholarpedia, vol.3, issue.6, pp.125-137, 2001. ,
DOI : 10.4249/scholarpedia.5187
Universal OWL Axiom Enrichment for Large Knowledge Bases, Knowledge Engineering and Knowledge Management -18th International Conference, pp.57-71, 2012. ,
DOI : 10.1007/978-3-642-33876-2_8
Possibility Theory?An Approach to Computerized Processing of Uncertainty, 1988. ,
Cluster analysis of multivariate data: Efficiency vs. interpretability of classifications, Biometrics, vol.21, pp.768-769, 1965. ,
, 2014, Perspectives on Ontology Learning. Studies on the Semantic Web
Ontology learning for the Semantic Web, IEEE Intelligent Systems, vol.16, issue.2, pp.72-79, 2001. ,
DOI : 10.1109/5254.920602
Learning Membership Functions for Fuzzy Sets through Modified Support Vector Clustering, Fuzzy Logic and Applications -10th International Workshop Proceedings (Lecture Notes in Computer Science), pp.52-59, 2013. ,
DOI : 10.1007/978-3-319-03200-9_6
A Survey on Fuzzy Implication Functions, IEEE Transactions on Fuzzy Systems, vol.15, issue.6, pp.1107-1121, 2007. ,
DOI : 10.1109/TFUZZ.2007.896304
Silhouettes: A graphical aid to the interpretation and validation of cluster analysis, J. Comput. Appl. Math, vol.2087, pp.53-650377, 1987. ,
pFOIL-DL, Proceedings of the 30th Annual ACM Symposium on Applied Computing , SAC '15, pp.345-352, 2015. ,
DOI : 10.1016/S0019-9958(65)90241-X
Partial Matchmaking using Approximate Subsumption, Proceedings of the Twenty-Second AAAI Conference on Artificial Intelligence, pp.1459-1464, 2007. ,
Dynamically Time-Capped Possibilistic Testing of SubClassOf Axioms Against RDF Data to Enrich Schemas, Proceedings of the 8th International Conference on Knowledge Capture, 2015. ,
Possibilistic Testing of OWL Axioms Against RDF Data, International Journal of Approximate Reasoning, vol.91, pp.114-130, 2017. ,
Testing OWL Axioms Against RDF Facts: A possibilistic approach, Knowledge Engineering and Knowledge Management -19th International Conference Proceedings (Lecture Notes in Artificial Intelligence), Krzysztof Janowicz, pp.519-530978, 2014. ,