Abstract
Conceptual data analysis has been extensively exploited to support Ontology Learning, Information Retrieval, and so on. This work emphasizes the relevant role of uncertainty in the conceptual data analysis. Specifically, Fuzzy Conceptual Data Analysis has been exploited to address two Enterprise Knowledge Management methodologies: domain ontology learning and ontology merging.
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De Maio, C., Fenza, G., Loia, V., Salerno, S. (2013). Fuzzy Conceptual Data Analysis Applied to Knowledge Management. In: Seising, R., Trillas, E., Moraga, C., Termini, S. (eds) On Fuzziness. Studies in Fuzziness and Soft Computing, vol 298. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35641-4_19
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DOI: https://doi.org/10.1007/978-3-642-35641-4_19
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-35640-7
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