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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.
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https://hal.archives-ouvertes.fr/hal-01416973
Contributor : Olivier Pivert <>
Submitted on : Thursday, December 15, 2016 - 10:33:00 AM
Last modification on : Friday, March 6, 2020 - 4:46:02 PM

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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. ⟨10.1109/FUZZ-IEEE.2016.7737915⟩. ⟨hal-01416973⟩

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