Clustering Users’ Requirements Schemas

Nouha Arfaoui, Jalel Akaichi


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.


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Paper Citation

in Harvard Style

Arfaoui N. and Akaichi J. (2014). Clustering Users’ Requirements Schemas . In Proceedings of 3rd International Conference on Data Management Technologies and Applications - Volume 1: DATA, ISBN 978-989-758-035-2, pages 15-21. DOI: 10.5220/0004991100150021

in Bibtex Style

author={Nouha Arfaoui and Jalel Akaichi},
title={Clustering Users’ Requirements Schemas},
booktitle={Proceedings of 3rd International Conference on Data Management Technologies and Applications - Volume 1: DATA,},

in EndNote Style

JO - Proceedings of 3rd International Conference on Data Management Technologies and Applications - Volume 1: DATA,
TI - Clustering Users’ Requirements Schemas
SN - 978-989-758-035-2
AU - Arfaoui N.
AU - Akaichi J.
PY - 2014
SP - 15
EP - 21
DO - 10.5220/0004991100150021