Abstract
Ontologies based on Description Logics (DLs) have proved to be effective in formally sharing knowledge across semantic technologies, e.g. Semantic Web, Natural Language Processing, Text Analytics, Business intelligence. Our main goal is analysing ontology construction considering vagueness. We have had the extension of ontologies with Fuzzy Logic capabilities which plan to make proper backgrounds for ontology driven reasoning and argumentation on vague and imprecise domains.
This presentation conceptualises learning from fuzzy classes using the Inductive Logic Programming framework. Then, employs Description Logics in characterising and analysing fuzzy statements. And finally, provides a conceptual framework describing fuzzy concept learning in ontologies using the Inductive Logic Programming.
This presentation conceptualises learning from fuzzy classes using the Inductive Logic Programming framework. Then, employs Description Logics in characterising and analysing fuzzy statements. And finally, provides a conceptual framework describing fuzzy concept learning in ontologies using the Inductive Logic Programming.
| Original language | English |
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| Publication date | 9 Jan 2015 |
| Publication status | Published - 9 Jan 2015 |
| Event | Revealing Hidden Knowledge Symposium - Copenhagen Business School , Copenhagen, Denmark Duration: 9 Jan 2015 → … |
Conference
| Conference | Revealing Hidden Knowledge Symposium |
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| Location | Copenhagen Business School |
| Country/Territory | Denmark |
| City | Copenhagen |
| Period | 09/01/2015 → … |