Title :
An Alternative Extension of the FCM Algorithm for Clustering Fuzzy Databases
Author :
Touzi, Amel Grissa
Author_Institution :
Dept. of Technol. of Inf. & Commun., Ecole Nat. d´´Ing. de Tunis, Tunis, Tunisia
Abstract :
Several real applications need to manage fuzzy information. Among the languages proposed for this type of data, the Fuzzy SQL (FSQL) language had a great success, seen its great power of modeling and it´s an extension of the well-known SQL language. In this paper, we propose an alternative for FCM algorithm For Fuzzy Database describe with FSQL. The conventional fuzzy clustering algorithms form fuzzy clusters so as to minimize the total distance from cluster centers to data points. However, they cannot be applied in the case where the data vectors are described with FSQL is given. To concretize our approach we used the BDRF described with the GEFRED model, which is supporting the FSQL language.
Keywords :
SQL; fuzzy set theory; pattern clustering; relational databases; BDRF; Fuzzy SQL language; GEFRED model; fuzzy c-means algorithm; fuzzy database clustering; Clustering algorithms; Conference management; Data analysis; Data mining; Databases; Fuzzy sets; Information management; Knowledge management; Pattern analysis; Technology management; FCM; Fuzzy DB; Fuzzy SQL; GEFRED model;
Conference_Titel :
Advances in Databases Knowledge and Data Applications (DBKDA), 2010 Second International Conference on
Conference_Location :
Menuires
Print_ISBN :
978-1-4244-6081-6
DOI :
10.1109/DBKDA.2010.35
