Abstract
The paper proposes level-based approximate reasoning on a fuzzy ontology as a modeling framework to support the creation and retrieval of Volunteered Geographic Information (VGI) affected by observation deficiencies causing both uncertainty and fuzziness. The paper recalls the inadequacy of classic ontologies to create VGI, the limitation of the use of fuzzy ontologies to model both fuzziness and uncertainty, and proposes level based reasoning to answer user queries on a VGI collection supported by a fuzzy ontology.
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CITATION STYLE
Bordogna, G., & Sterlacchini, S. (2017). Volunteered geographic information management supported by Fuzzy ontologies and level-based approximate reasoning. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10350 LNCS, pp. 466–476). Springer Verlag. https://doi.org/10.1007/978-3-319-60042-0_51
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