Ontology-Based Fuzzy-Syllogistic Reasoning

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Date

2015

Authors

Kumova, Bora İsmail

Journal Title

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Publisher

Springer Verlag

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Green Open Access

Yes

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No
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Abstract

We discuss the Fuzzy-Syllogistic System (FSS) that consists of the well-known 256 categorical syllogisms, namely syllogistic moods, and Fuzzy- Syllogistic Reasoning (FSR), which is an implementation of the FSS as one complex approximate reasoning mechanism, in which the 256 moods are interpreted as fuzzy inferences. Here we introduce a sample application of FSR as ontology reasoner. The reasoner can associate up to 256 possible fuzzyinferences with truth ratios in [0,1] for every triple concept relationship of the ontology. We further discuss a transformation technique, by which the truth ratio of a fuzzy-inference can increase, by adapting the fuzzy-quantifiers of a fuzzy-inference to the syllogistic logic of the sample propositions.

Description

28th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2015; Seoul; South Korea; 10 June 2015 through 12 June 2015

Keywords

Approximate reasoning, Categorical syllogisms, Ontologies, Fuzzy inference, Fuzzy inference, Categorical syllogisms, Ontologies, Approximate reasoning

Fields of Science

0202 electrical engineering, electronic engineering, information engineering, 06 humanities and the arts, 02 engineering and technology, 0603 philosophy, ethics and religion

Citation

Zarechnev, M., and Kumova, B. İ. (2015). Ontology-based fuzzy-syllogistic reasoning. Lecture Notes in Computer Science, 9101, 179-188. doi:10.1007/978-3-319-19066-2_18

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N/A

Scopus Q

Q3
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OpenCitations Citation Count
3

Source

Lecture Notes in Computer Science

Volume

9101

Issue

Start Page

179

End Page

188
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Scopus : 3

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Mendeley Readers : 3

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3

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788

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435

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