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Original Research

JPAS. 2020; 20(1): 48-57


Modelling Uncertainty in Ontology for The Semantic Web Using Vague Graph Theory

Amina Hassan Abubakar, Armand Florentin Donfack Kana.




Abstract

Ontology is viewed as an explicit representation of conceptualization. It consists of a set
of concepts, their definitions and their interrelationships. Ontologies are used to unambiguously model an area of knowledge by “semantically” defining the concepts and their
relationships in a given domain in a way that can be understood by both humans and
machines. One of the major limitations of traditional ontology formalism is its lack of
support for the representation of uncertainty and imprecision. As a result, they cannot
handle incomplete or partial knowledge. Attempts have been made by other researchers
to address this problem using algebraic methods, such as rough sets, soft sets, fuzzy sets,
and probabilistic approaches. However, the conceptualization of the proposed solutions
in those approaches is not always the same as how ontologies are actually implemented.
Ontology languages [such as Resource Description Framework (RDF), RDF Schema (RDFS),
and Web Ontology Language (OWL)] are used for expressing ontologies for Semantic
Web (SW) in a crisp manner. This paper proposed a vague graph approach to formalize
uncertainty in ontology for the SW. The paper extended RDFvg and RDFSvg, respectively,
where both syntactic and semantic extensions of the languages are proposed. Similarly, a
description of vague OWL was provided as OWLvg.

Key words: Uncertainty, RDFvg, RDFSvg, OWLvg






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