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An Ontology And Conceptual Graph Based Best Matching Algorithm For Context-aware Applications

Context-aware computing is based on using knowledge about the current context.
Interpretation of current context to an understandable knowledge is carried out
by reasoning over context and in some cases by matching the current context
with the desired context. In this thesis we concentrated on context matching issue
in context-aware computing domain. Context matching can be done in various
ways like it is done in other matching processes. Our matching approach is best
matching in order to generate granular similarity results and not to be limited to
Boolean values. We decided to use Ontology as the encoded domain knowledge
for our matching method. Context matching method is related to the method that
we represent context. We selected conceptual graphs to represent the context. We
proposed a generic algorithm for context matching based on the ontological
information that benefit from the conceptual graph theory and its advantages.

Identiferoai:union.ndltd.org:METU/oai:etd.lib.metu.edu.tr:http://etd.lib.metu.edu.tr/upload/12613216/index.pdf
Date01 May 2011
CreatorsKoushaeian, Reza
ContributorsKocyigit, Altan
PublisherMETU
Source SetsMiddle East Technical Univ.
LanguageEnglish
Detected LanguageEnglish
TypeM.S. Thesis
Formattext/pdf
RightsTo liberate the content for public access

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