2011 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2011) 2011
DOI: 10.1109/fuzzy.2011.6007623
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Cited by 10 publications
(4 citation statements)
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“…In [16], the fuzzy closure approach has been further investigated and compared to the simpler α-cut approach with experimentation using the Gene Ontology [22].…”
Section: B Creating Fuzzy Ontologiesmentioning
confidence: 99%
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“…In [16], the fuzzy closure approach has been further investigated and compared to the simpler α-cut approach with experimentation using the Gene Ontology [22].…”
Section: B Creating Fuzzy Ontologiesmentioning
confidence: 99%
“…Each formal concept it creates contains two components, the set of instance objects referred to as its extent, and the set of attributes describing the objects referred to as its intent. Fuzzy formal concept analysis (FFCA) is a natural extension for creating fuzzy ontologies [16]. The main difference is that in the formal context an attribute may only be partially associated with an object, i.e., an attribute has a degree of association or membership when used to describe the object.…”
Section: B Creating Fuzzy Ontologiesmentioning
confidence: 99%
“…Castano et al . (2008) presented a tool for mapping validation with the help of probabilistic reasoning. The idea is to assume a semantic interpretation of ontology mappings as probabilistic and hypothetical relations among ontology elements in order to build a unique distributed knowledge base from the two independent ontologies and, subsequently, check for inconsistencies.…”
Section: Applications and Other Issues Of Fuzzy Ontologiesmentioning
confidence: 99%
“…Constructing fuzzy ontologies based on formal concept analysis theory (Quan et al, 2006a(Quan et al, , 2006bChen et al, 2009;De Maio et al, 2009;Cross & Kandasamy, 2011) Constructing fuzzy ontologies from fuzzy database models (Blanco et al, 2005(Blanco et al, , 2008Ma et al, , 2010Ma et al, , 2011aMa et al, , 2011bZhang et al, 2008aZhang et al, , 2008bZhang et al, , 2011bZhang et al, , 2013aZhang et al, , 2013bZhang et al, , 2015) Constructing fuzzy ontologies from other data sources such as fuzzy narrower terms, fuzzy relations, among others (Widyantoro & Yen, 2001a, 2001bNikravesh et al, 2004;Angryk et al, 2006;Ceravolo et al, 2006;Nováček & Smrž, 2006;Ling et al, 2007;Tafazzoli & Sadjadi, 2008;Ghorbel et al, 2010;Inyaem et al, 2010;Alexopoulos et al, 2012) Querying over lightweight fuzzy DL ontologies (Straccia, 2006c;Pan et al, 2007Pan et al, , 2008 Querying over expressive fuzzy DL ontologies (Mailis et al, 2007;Cheng et al, 2008bCheng et al, , 2009aCheng et al, , 2009b Querying over fuzzy ontologies based on fuzzy relational databases (Buche et al, 2005;Bahri et al, 2009) Other fuzzy ontology query approaches (Widyantoro & Yen, 2001a…”
Section: Construction Query and Storagementioning
confidence: 99%