Abstract
This paper shows problems with combination of rule induction and attribute-oriented generalization, where if the given hierarchy includes inconsistencies, then application of hierarchical knowledge generates inconsistent rules. Then, we introduce two approaches to solve this problem, one process of which suggests that combination of rule induction and attribute-oriented generalization can be used to validate concept hiearchy. Interestingly, fuzzy linguistic variables play an important role in solving these problems.
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Tsumoto, S. (2002). Validation of Concept Representation with Rule Induction and Linguistic Variables. In: Lin, T.Y., Yao, Y.Y., Zadeh, L.A. (eds) Data Mining, Rough Sets and Granular Computing. Studies in Fuzziness and Soft Computing, vol 95. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-1791-1_4
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DOI: https://doi.org/10.1007/978-3-7908-1791-1_4
Publisher Name: Physica, Heidelberg
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Online ISBN: 978-3-7908-1791-1
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