Reasoning within extended fuzzy description logic

Lu, Jianquan; Li, Yanhui; Zhou, Bo; Kang, Dong-Wook

doi:10.1016/j.knosys.2008.04.010

Cited by 12 publications

(9 citation statements)

References 19 publications

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“…Tresp [52] considered fuzzy ALC extended with a special form of modifiers, which are a combination of two linear functions. A fuzzy extension of the ALC language is also considered by Straccia [46] and Lu et al [35]. Reasoning algorithms for the problem of crisp entailment and subsumption were provided.…”

Section: Discussionmentioning

confidence: 99%

Expressive fuzzy description logics over lattices

Jiang

Tang

Wang

et al. 2010

Knowledge-Based Systems

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Section: Discussionmentioning

confidence: 99%

Expressive fuzzy description logics over lattices

Jiang

Tang

Wang

et al. 2010

Knowledge-Based Systems

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“…It is necessary to merge knowledge in an enterprise, not only for concrete domains, but also for fuzzy domains. Recently approaches have been reported for extending and reasoning with ontologies in fuzzy domains [28][29][30] .…”

Section: Literature Surveymentioning

confidence: 99%

Description logic–based knowledge merging for concrete- and fuzzy-domain ontologies

Kumar

Harding

2015

Proceedings of the Institution of Mechanical Engineers, Part B:

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“…This construction models graded or fuzzy concepts (Lu, et al, 2008) through the existing logical structure without introducing additional concept types.…”

Section: Graded Conceptsmentioning

confidence: 99%

Designing Visual Languages for Description Logics

Gaines

2008

J of Log Lang and Inf

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Semantic networks were developed in cognitive science and artificial intelligence studies as graphical knowledge representation and inference tools emulating human thought processes. Formal analysis of the representation and inference capabilities of the networks modeled them as subsets of standard first-order logic (FOL), restricted in the operations allowed in order to ensure the tractability that seemed to characterize human reasoning capabilities. The graphical network representations were modeled as providing a visual language for the logic. Sub-sets of FOL targeted on knowledge representation came to be called description logics, and research on these logics has focused on issues of tractability of subsets with differing representation capabilities, and on the implementation of practical inference systems achieving the best possible performance. Semantic network research has kept pace with these developments, providing visual languages for knowledge entry, editing, and presenting the results of inference, that translate unambiguously to the underlying description logics. This paper discusses the design issues for such semantic network formalisms, and illustrates them through detailed examples of significant generic knowledge structures analyzed in the literature, including determinables, contrast sets, genus/differentiae, taxonomies, faceted taxonomies, cluster concepts, family resemblances, graded concepts, frames, definitions, rules, rules with exceptions, essence and state assertions, opposites and contraries, relevance, and so on. Such examples provide important test material for any visual language formalism for logic.

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Reasoning within extended fuzzy description logic

Cited by 12 publications

References 19 publications

Expressive fuzzy description logics over lattices

Expressive fuzzy description logics over lattices

Description logic–based knowledge merging for concrete- and fuzzy-domain ontologies

Designing Visual Languages for Description Logics

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