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Title:
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FUZZY APPROXIMATE DEPENDENCIES OVER IMPRECISE DOMAINS. AN EXAMPLE IN SOIL DATA MANAGEMENT |
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Author(s):
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J. Calero , J.m. Serrano , D. Sánchez , M.a. Vila , G. Delgado |
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ISBN:
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972-98947-3-6 |
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Editors:
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Nuno Guimarães and Pedro Isaías |
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Year:
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2004 |
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Edition:
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Single |
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Keywords:
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Fuzzy approximate dependencies, fuzzy data mining, imprecise domains, fuzzy similarity relations, fuzzy databases. |
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Type:
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Full Paper |
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First Page:
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1396 |
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Last Page:
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1403 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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Fuzzy databases are commonly used when managing imprecise or uncertain information as, for example, soil color data, that is usually affected by inherent imprecision factors. In many occasions, a set of semantic relations between real problems data can be modelled by means of fuzzy similarity relations. Also, attributes over numeric domains can be transformed, if we define adequate sets of linguistic labels, in order to reduce granularity. Data mining tools, as association rules and approximate dependencies, have been proven effective and useful when users are looking for implicit or non-intuitive relations between data. Nevertheles, data mining techniques must be extended in order to allow this imprecise or uncertain data. Several approaches can be found in the literature with this aim. In this work, we comment some of them and apply both crisp and fuzzy techniques over a soil database, comparing obtained results with domain experts aid. |
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