Enhancing Flexibility and Expressivity of Contextual Hierarchies

Abstract : Data warehouses are nowadays extensively used to perform analyses on huge volume of data. This success is partly due to the capacity of considering data at several granularity levels thanks to the use of hierarchies. However, in previous work, we showed that the experts' knowledge were not much considered in the generalization process. To overcome this drawback, we introduced a new category of hierarchies, namely the contextual hierarchies. Unfortunately, in contrast to the complexity of expert knowledge that should be considered, the knowledge definition process was too rigid. In this paper, we extend these hierarchies and their related techniques to drastically increase their flexibility and expressivity. To this purpose, we adopt a fuzzy-based methodology which allows to express expert knowledge in a very convenient way. Experiment results obtained on synthetic datasets show that the contextual generalization process is very fast and can thus be used in practice.
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Communication dans un congrès
FUZZ: Fuzzy Systems, Jun 2012, Brisbane, QLD, Australia. 21th IEEE International Conference on Fuzzy Systems, pp.1-8, 2012, 〈10.1109/FUZZ-IEEE.2012.6251176〉
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https://hal-lirmm.ccsd.cnrs.fr/lirmm-00798078
Contributeur : Pascal Poncelet <>
Soumis le : vendredi 8 mars 2013 - 03:37:49
Dernière modification le : jeudi 19 avril 2018 - 14:38:02

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Yoann Pitarch, Cécile Favre, Anne Laurent, Pascal Poncelet. Enhancing Flexibility and Expressivity of Contextual Hierarchies. FUZZ: Fuzzy Systems, Jun 2012, Brisbane, QLD, Australia. 21th IEEE International Conference on Fuzzy Systems, pp.1-8, 2012, 〈10.1109/FUZZ-IEEE.2012.6251176〉. 〈lirmm-00798078〉

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