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Erschienen in:
Challenges in Bridging Social Semantics and Formal Semantics on the Web Kapitel lesen Erstes Kapitel lesen

2014 | OriginalPaper | Buchkapitel

Combining Fuzzy Ontology Reasoning and Mamdani Fuzzy Inference System with HyFOM Reasoner

verfasst von : Cristiane A. Yaguinuma, Walter C. P. Magalhães Jr., Marilde T. P. Santos, Heloisa A. Camargo, Marek Reformat

Erschienen in: Enterprise Information Systems

Verlag: Springer International Publishing

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Abstract

Representing and processing imprecise knowledge has been a requirement for a number of applications. Some real-world domains as well as human subjective perceptions are intrinsically fuzzy, therefore conventional formalisms may not be sufficient to capture the intended semantics. In this sense, fuzzy ontologies and Mamdani fuzzy inference systems have been successfully applied for knowledge representation and reasoning. Combining their reasoning approaches can lead to inferences involving fuzzy rules and numerical properties from ontologies, which can be required to perform other fuzzy ontology reasoning tasks such as the fuzzy instance check. To address this issue, this paper describes the HyFOM reasoner, which follows a hybrid architecture to combine fuzzy ontology reasoning with Mamdani fuzzy inference system. A real-world case study involving the domain of food safety is presented, including comparative results with a state-of-the-art fuzzy description logic reasoner.

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Metadaten
Titel
Combining Fuzzy Ontology Reasoning and Mamdani Fuzzy Inference System with HyFOM Reasoner
verfasst von
Cristiane A. Yaguinuma
Walter C. P. Magalhães Jr.
Marilde T. P. Santos
Heloisa A. Camargo
Marek Reformat
Copyright-Jahr
2014
Buch
Enterprise Information Systems

Print ISBN: 978-3-319-09491-5

Electronic ISBN: 978-3-319-09492-2

Copyright-Jahr: 2014

DOI
https://doi.org/10.1007/978-3-319-09492-2_11