Authors:
Nouha Arfaoui
and
Jalel Akaichi
Affiliation:
Institut Supérieur de Gestion, Tunisia
Keyword(s):
Star Schema, User Requirement, Clustering, k-Mode Extension, Ontology.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Biomedical Engineering
;
Business Analytics
;
Data Engineering
;
Data Mining
;
Data Warehouse Management
;
Databases and Information Systems Integration
;
Datamining
;
Dimensional Modeling
;
Enterprise Information Systems
;
Health Information Systems
;
Sensor Networks
;
Signal Processing
;
Soft Computing
Abstract:
Data Mining proposes different techniques to deal with data. In our work, we suggest the use of clustering technique since we want grouping the schemas into clusters according to their similarity. This technique is applied to variety type of variables. We focus on categorical data. Many algorithms are proposed, but no one of them takes into consideration the semantic aspect. For this reason, and in order to ensure a good clustering of the schemas of the users’ requirements, we extend the k-mode algorithm by modifying its dissimilarity measure. The schemas within each cluster will be merged to construct the schemas of the data mart.