By Zongmin Ma
This e-book is going to nice intensity in regards to the quickly becoming subject of applied sciences and ways of fuzzy common sense within the Semantic internet. the subjects of this publication contain fuzzy description logics and fuzzy ontologies, queries of fuzzy description logics and fuzzy ontology wisdom bases, extraction of fuzzy description logics and ontologies from fuzzy information versions, garage of fuzzy ontology wisdom bases in fuzzy databases, fuzzy Semantic internet ontology mapping, and fuzzy ideas and their interchange within the Semantic internet. The publication goals to supply a unmarried list of present study within the fuzzy wisdom illustration and reasoning for the Semantic net. the target of the booklet is to supply the state-of-the-art details to researchers, practitioners and graduate scholars of the internet intelligence and while serve the information and information engineering specialist confronted with non-traditional functions that make the applying of traditional techniques tough or impossible.
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Additional info for Fuzzy Knowledge Management for the Semantic Web
Sample text
2011b; Zhang and Ma 2013). Then, we provide a formal definition of fuzzy UML models, give the semantic interpretation of fuzzy UML models, and show an example of a fuzzy UML model (Ma et al. 2011b; Zhang and Ma 2013). All of these are the basic of extracting fuzzy Description Logics and fuzzy ontologies from fuzzy UML models as will be introduced in the later chapters. 1 Fuzzy Class An object, which is an entity of the real world, is fuzzy because of a lack of information. Formally, objects that have at least one attribute whose value is a fuzzy set are fuzzy objects.
Dynamic attributes), a set FTf of datatype symbols, a set FCf of fuzzy class symbols, a set FHf of fuzzy hierarchy symbols, a set FGf of fuzzy aggregation symbols, a set FDf of fuzzy dependency symbols, a set FSf of fuzzy association symbols, and a set FRf of role symbols. Here it should be noted that: • • • • – A method in FMf is the form of f(P1, …, Pm) : R, where f is the name of the method, P1,…,Pm are types of m parameters, and R is the type of the result. – Each attribute FA [ FAf is associated with a domain FT [ FTf, and each fuzzy domain symbol FT has an associated predefined basic domain and the various basic domains are usually assumed to be pairwise disjoint.
In more detail, also based on possibility distribution theory, Ma et al. (2004) introduced fuzzy object-oriented database models, some major notions such as objects, classes, objects-classes relationships and subclass/superclass relationships were extended under fuzzy information environment. Moreover, other fuzzy extensions of object-oriented databases were developed. In Marín et al. (2000, 2001), fuzzy types were added into fuzzy objectoriented databases to manage vague structures. The fuzzy relationships and fuzzy behavior in fuzzy object-oriented database models were discussed in Cross (2001) and Gyseghem and Caluwe (1995).