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Summarizing Multidimensional Databases Using Fuzzy Rules

Abstract : In the context of multidimensional data, OLAP tools are appropriate for the navigation in the data, aiming at discovering pertinent and abstract knowledge. However, due to the size of the dataset, a systematic and exhaustive exploration is not feasible. Therefore, the problem is to design automatic tools to ease the navigation in the data and their visualization. In this paper, we present a novel approach allowing to build automatically blocks of similar values in a given data cube and to associate these blocks with rules. Our method is based on a levelwise algorithm (a la Apriori) and on the fuzzy set theory. The latter is considered here due to the fact that some of the blocks computed by our algorithm can overlap.
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https://hal-lirmm.ccsd.cnrs.fr/lirmm-00108883
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Yeow Wei Choong, Anne Laurent, Dominique Laurent, Pierre Maussion. Summarizing Multidimensional Databases Using Fuzzy Rules. IPMU: Information Processing and Management of Uncertainty, Jul 2004, Perugia, Italy. pp.99-106. ⟨lirmm-00108883⟩

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