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Article type: Research Article
Authors: Sun, ShengTao;
Affiliations: College of Information Science and Engineering, Yan Shan University, Hebei Province, P.R. China | Center of Earth Observation and Digital Earth, Chinese Academy of Sciences, Beijing, P.R. China
Note: [] Corresponding author. ShengTao Sun, Department of Computer, College of Information Science and Engineering, Yan Shan University, No. 438, Hebei Avenue, Qinhuangdao City, 066004 Hebei Province, P.R. China. E-mail: xysst@ysu.edu.cn
Abstract: This paper focuses on the application of possibilistic logic in the extension of ontology for uncertain knowledge description. It proposes an uncertain semantic relationship description method based on possibilistic logic and probabilistic statistics. This novel method combines the advantages of subjective valuation and objective statistics, which makes the representation and inference of uncertainty in ontologies more flexible and reasonable. Finally, we apply this quantitative measurement to describe incomplete (uncertain) knowledge and imprecise (vague) information of uncertain knowledge in ontology knowledgebase.
Keywords: Semantic ontology, uncertain knowledge description, quantitative measurement, possibilistic logic, probabilistic statistics
DOI: 10.3233/IFS-120695
Journal: Journal of Intelligent & Fuzzy Systems, vol. 25, no. 4, pp. 931-940, 2013
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