6533b825fe1ef96bd128340b

RESEARCH PRODUCT

How to Enrich Description Logics with Fuzziness

Christophe CruzMartin Unold

subject

[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI]Theoretical computer science[ INFO ] Computer Science [cs]Relation (database)Process (engineering)Computer scienceMathematics::General Mathematics0102 computer and information sciences02 engineering and technology[INFO] Computer Science [cs]01 natural sciencesFuzzy logicTask (project management)[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]Knowledge-based systemsFuzzy Description LogicDescription logicComputer Science::Logic in Computer Science0202 electrical engineering electronic engineering information engineering[INFO]Computer Science [cs][ INFO.INFO-AI ] Computer Science [cs]/Artificial Intelligence [cs.AI]Semantic WebSemantic WebUncertaintyTransformation (function)TheoryofComputation_MATHEMATICALLOGICANDFORMALLANGUAGES010201 computation theory & mathematics020201 artificial intelligence & image processingComputingMethodologies_GENERALHardware_LOGICDESIGN

description

International audience; The paper describes the relation between fuzzy and non-fuzzy description logics. It gives an overview about current research in these areas and describes the difference between tasks for description logics and fuzzy logics. The paper also deals with the transformation properties of description logics to fuzzy logics and backwards. While the process of transformation from a description logic to a fuzzy logic is a trivial inclusion, the other way of reducing information from fuzzy logic to description logic is a difficult task, that will be topic of future work.

yearjournalcountryeditionlanguage
2017-07-18
https://hal.archives-ouvertes.fr/hal-01689809