Research >> Approximate Ontologies
Research Project: Formal Treatment of Imprecision in the Semantic Web Ontologies
The goal of the project is to formally capture the imprecision and uncertainty that often exists in ontologies.
The desired result is a mathematical framework capable of treating such types of uncertainty as: granularity, vagueness and incompleteness.
The framework is supposed to be used to formally approximate ontological knowledge (concepts and relationships) in crisp approximation spaces.
Automated approximate reasoning is expected to be supported by retaining the logical (Description Logics) foundations of formal ontologies.
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Main phases of the project:
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- Provide formal representation of approximate ontological building blocks (rough (fuzzy) sets, rough mereology)
- Develop representation and methods for constructing approximate conceptual hierarchies (approximate concept graphs)
- Develop necessary extensions for Description Logics and translation methods (approximate DLs)
- Provide computational methods (quality assessment, approximate reasoning)
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Project description (NSF proposal submitted Dec 2006):
.pdf
.ps
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Documents (publications, drafts, technical reports):
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- January 2007: "Interval Rough Mereology for Approximating Hierarchical Knowledge",
submitted for review to Rough Sets and Knowledge Technology at Joint Rough Set Symposium, May 2007
.pdf
- June 2006: "Fuzzy Rough Approach to Handling Imprecision in the Semantic Web Ontologies", NAFIPS'06
.pdf
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News:
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- December 2006: Full research proposal
(.pdf) is submitted to the NSF computational mathematics
program.
- June 2006: The paper "Fuzzy Rough Approach to Handling Imprecision in the Semantic Web Ontologies" received
"Top 5 Student Paper Award"
at NAFIPS 2006
- March 2006: The paper "Fuzzy Rough Approach to Handling Imprecision in the Semantic Web Ontologies"
.pdf is accepted to the North American
Fuzzy Information Processing Society Conference (NAFIPS 2006). The conference will be hosted in Montreal, Quebec, Canada in June 2006
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