2016
DOI: 10.1007/s13218-016-0459-3
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Decidability and Complexity of Fuzzy Description Logics

Abstract: Fuzzy description logics (FDLs) have been introduced to represent concepts for which membership cannot be determined in a precise way, i.e., where instead of providing a strict border between being a member and not being a member, it is more appropriate to model a gradual change from membership to nonmembership. First approaches for reasoning in FDLs where based either on a reduction to reasoning in classical description logics (DLs) or on adaptations of reasoning approaches for DLs to the fuzzy case. However,… Show more

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Cited by 13 publications
(7 citation statements)
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“…However, the authors of [29, 32] show some interesting conditions under which decidability is still guaranteed. They show that if the knowledge bases are acyclic, the proof of the correctness of the tableau‐based algorithms is valid and under product fuzzy logic and the proof is only valid if we only consider unfoldable knowledge bases.…”
Section: Resultsmentioning
confidence: 99%
“…However, the authors of [29, 32] show some interesting conditions under which decidability is still guaranteed. They show that if the knowledge bases are acyclic, the proof of the correctness of the tableau‐based algorithms is valid and under product fuzzy logic and the proof is only valid if we only consider unfoldable knowledge bases.…”
Section: Resultsmentioning
confidence: 99%
“…Standard reasoning tasks as well as conjunctive query answering have been considered and implemented in several reasoners and ontology editor plug-ins. We limit ourselves to mentioning that essentially every truly fuzzy DL that allows for expressing terminological cycles is undecidable, see the discussion in a recent project report [28]. For a concise overview of fuzzy DLs, we refer the interested reader to a recent survey article [74], which also contains information on diverse applications of fuzzy DLs.…”
Section: Extensions Of Standard Ontology Languagesmentioning
confidence: 99%
“…Our initial investigations within this project produced undecidability results for several fuzzy DLs with GCIs and showed that the decidable cases are actually not truly fuzzy since decidability can be obtained by a reduction to the crisp case [8,13,17,21]. Since within our project in HAEC we did not have enough time for a thorough analysis of the decidability status of fuzzy DLs, these initial results were the starting point for a separate research project funded by DFG and dedicated to investigating fuzzy DLs [9]. This project achieved an almost complete classification of the border between decidability and undecidability for fuzzy DLs with GCIs.…”
Section: Admitting Vagueness For Ontology-based Context Recognitionmentioning
confidence: 99%