Title: Model-driven data mining engineering: from solution-driven implementations to 'composable' conceptual data mining models

Authors: Alfredo Cuzzocrea, Jose-Norberto Mazon, Juan Trujillo, Jose Zubcoff

Addresses: ICAR-CNR and University of Calabria, Via P. Bucci, 41C, Rende, 87036 Cosenza, Italy. ' Department of Software and Computing Systems, University of Alicante, Apartado de Correos 99, E-03080 Alicante, Spain. ' Department of Software and Computing Systems, University of Alicante, Apartado de Correos 99, E-03080 Alicante, Spain. ' Department of Sea Sciences and Applied Biology, University of Alicante, Apartado de Correos 99, E-03080 Alicante, Spain

Abstract: Data mining lacks a general modelling architecture allowing analysts to consider and interpret it as a truly software-engineering process, which would be beneficial for a wide spectrum of modern application scenarios. Bearing this in mind, in this paper, we propose an innovative model-driven engineering approach of data mining whose main goal consists in overcoming well-recognised limitations of actual approaches. The cornerstone of our proposal relies on the definition of a set of suitable model transformations which are able to automatically generate both the data under analysis, which are deployed via well-consolidated data warehousing technology and the analysis models for the target data mining tasks, which are tailored to a specific data-mining/analysis platform. These modelling tasks are now entrusted to the model-transformation scaffolds and rely on top of a well-defined reference architecture. The feasibility of our approach is finally demonstrated and validated by means of a comprehensive set of case studies.

Keywords: data mining; conceptual modelling; multidimensional modelling; model-driven engineering; model transformations; data warehousing.

DOI: 10.1504/IJDMMM.2011.041808

International Journal of Data Mining, Modelling and Management, 2011 Vol.3 No.3, pp.217 - 251

Published online: 26 Feb 2015 *

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