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Reducing the size of the optimization problems in fuzzy ontology reasoning
- Source :
- International Workshop on Uncertainty Reasoning for the Semantic Web (URSW-15), pp. 54–59, Bethlehem, USA, October 12, 2015, info:cnr-pdr/source/autori:Bobillo F.; Straccia U./congresso_nome:International Workshop on Uncertainty Reasoning for the Semantic Web (URSW-15)/congresso_luogo:Bethlehem, USA/congresso_data:October 12, 2015/anno:2015/pagina_da:54/pagina_a:59/intervallo_pagine:54–59
- Publication Year :
- 2015
-
Abstract
- Fuzzy ontologies allow the representation of imprecise structured knowledge, typical in many real-world application domains. A key factor in the practical success of fuzzy ontologies is the availability of highly optimized reasoners. This short paper discusses a novel optimization technique: a reduction of the size of the optimization problems obtained during the inference by the fuzzy ontology reasoner fuzzyDL.
- Subjects :
- Fuzzy Description Logics
ComputingMethodologies_GENERAL
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Journal :
- International Workshop on Uncertainty Reasoning for the Semantic Web (URSW-15), pp. 54–59, Bethlehem, USA, October 12, 2015, info:cnr-pdr/source/autori:Bobillo F.; Straccia U./congresso_nome:International Workshop on Uncertainty Reasoning for the Semantic Web (URSW-15)/congresso_luogo:Bethlehem, USA/congresso_data:October 12, 2015/anno:2015/pagina_da:54/pagina_a:59/intervallo_pagine:54–59
- Accession number :
- edsair.dedup.wf.001..9abae61ae1ac35f43fd6bc254cf17b20