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https://hdl.handle.net/11147/5479
Title: | Ontology-based fuzzy-syllogistic reasoning | Authors: | Zarechnev, Mikhail Kumova, Bora İsmail |
Keywords: | Approximate reasoning Categorical syllogisms Ontologies Fuzzy inference |
Publisher: | Springer Verlag | Source: | 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 | 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 | URI: | http://doi.org/10.1007/978-3-319-19066-2_18 http://hdl.handle.net/11147/5479 |
ISBN: | 9783319190655 | ISSN: | 0302-9743 1611-3349 |
Appears in Collections: | Computer Engineering / Bilgisayar Mühendisliği Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection |
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