Ontology-Based Fuzzy-Syllogistic Reasoning
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Date
2015
Authors
Kumova, Bora İsmail
Journal Title
Journal ISSN
Volume Title
Publisher
Springer Verlag
Open Access Color
Green Open Access
Yes
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Publicly Funded
No
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
WoS Q
N/A
Scopus Q
Q3

OpenCitations Citation Count
3
Source
Lecture Notes in Computer Science
Volume
9101
Issue
Start Page
179
End Page
188
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Citations
CrossRef : 3
Scopus : 3
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3
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788
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435
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