A Soft Computing Approach to Agile Business Intelligence

Abstract : In this paper, a novel approach is introduced to let users extract knowledge from a raw dataset in an intuitive way and using their own vocabulary. The inner structure of a raw data set is first identified using a clustering algorithm, structure on which specificity-driven measures are defined to extract the most informative knowledge. To let domain experts interact with the cluster-based structure and its embedded knowledge, a graphical visualisation is proposed as well as dedicated query operators.
Type de document :
Communication dans un congrès
25th IEEE International Conference on Fuzzy Systems (Fuzz-IEEE'16), Jul 2016, Vancouver, Canada. 2016, Proc. of the 25th IEEE International Conference on Fuzzy Systems (Fuzz-IEEE'16). <10.1109/FUZZ-IEEE.2016.7737915>
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https://hal.archives-ouvertes.fr/hal-01416973
Contributeur : Olivier Pivert <>
Soumis le : jeudi 15 décembre 2016 - 10:33:00
Dernière modification le : samedi 18 février 2017 - 01:09:46

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Grégory Smits, Olivier Pivert, Ronald R. Yager. A Soft Computing Approach to Agile Business Intelligence. 25th IEEE International Conference on Fuzzy Systems (Fuzz-IEEE'16), Jul 2016, Vancouver, Canada. 2016, Proc. of the 25th IEEE International Conference on Fuzzy Systems (Fuzz-IEEE'16). <10.1109/FUZZ-IEEE.2016.7737915>. <hal-01416973>

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