Modelling a Structure of a Fuzzy Data Warehouse
Applied Engineering
Volume 1, Issue 2, December 2017, Pages: 48-56
Received: Apr. 12, 2017; Accepted: Apr. 22, 2017; Published: Jun. 28, 2017
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Alain Kuyunsa Mayu, Faculty of Sciences, Regional Center for Doctoral Education in Mathematics and Computer Sciences, University of Kinshasa, Kinshasa, D. R. Congo
Nathanael Kasoro Mulenda, Faculty of Sciences, Department of Mathematics and Computer Sciences, University of Kinshasa, Kinshasa, D. R. Congo
Rostin Mabela Matendo, Faculty of Sciences, Department of Mathematics and Computer Sciences, University of Kinshasa, Kinshasa, D. R. Congo
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In this article, we represent the structure of a fuzzy data warehouse. The elements of classification to build the fuzzy data warehouse are presented through the three following tasks: identification of the target-attribute, identification of linguistic terms and definition of membership functions. From these tasks, we present an approach of a fuzzy data warehouse modelling. This allows us to integrate fuzzy logic without affecting the data warehouse base.
Target Attribute, Class Membership Attribute, Membership Degree, Membership Degree Attribute,Fuzzy Classification Table, Fuzzy Membership Table
To cite this article
Alain Kuyunsa Mayu, Nathanael Kasoro Mulenda, Rostin Mabela Matendo, Modelling a Structure of a Fuzzy Data Warehouse, Applied Engineering. Vol. 1, No. 2, 2017, pp. 48-56. doi: 10.11648/
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This article is an open access article distributed under the Creative Commons Attribution License ( which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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