Title: A support architecture to MDA contribution for data mining

Authors: Fatima Meskine; Safia Nait-Bahloul

Addresses: LITIO Laboratory, University Oran1, Ahmed Ben Bella, BP 1524, El-M'Naouer, Oran, Algeria; Department of Computer Science, Hassiba Benbouali University of Chlef, B.P 78C, Ouled Fares, 02180 Chlef, Algeria ' LITIO Laboratory, University Oran1, Ahmed Ben Bella, BP 1524, El-M'Naouer, Oran, Algeria

Abstract: The data mining process is the sequence of tasks applied to data, in order to discover relations between them to have knowledge. However, the data mining process lacks a formal specification that allows it to be modelled independently of platforms. Model driven architecture (MDA) is an approach for the development of software systems, based on the use of models to improve their productivity. Several research works have been elaborated to align the MDA approach with data mining on data warehouses, to specify the data mining process in a very high level of abstraction. In our work, we propose a support architecture that allows positioning these researches in different abstraction levels, on the basis of several criteria; with the aim to identify strengths for each level, in term of modelling; and to have a clear visibility on the MDA contribution for data mining.

Keywords: data mining; model driven architecture; MDA; data warehouses; UML profiles; data multidimensional model; transformation.

DOI: 10.1504/IJDMMM.2020.106723

International Journal of Data Mining, Modelling and Management, 2020 Vol.12 No.2, pp.207 - 236

Received: 07 Apr 2018
Accepted: 07 Dec 2018

Published online: 20 Apr 2020 *

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