Towards a model-driven engineering approach of data mining

Nowadays, data mining is based on low-level specications of the employed techniques typically bounded to a specic analysis platform. Therefore, data mining lacks a modelling architecture that allows analysts to consider it as a truly software-engineering process. Here, we propose a model-driven approach based on (i) a conceptual modelling framework for data mining, and (ii) a set of model transformations to automatically generate both the data under analysis (via data-warehousing technology) and the analysis models for data mining (tailored to a specic platform). Thus, analysts can concentrate on the analysis problem via conceptual data-mining models instead of low-level programming tasks related to the underlying-platform technical details. These tasks are now entrusted to the model-transformations scaffolding.

This work has been supported by the ESPIA (TIN2007-67078) project (Spanish Ministry of Education), and by the QUASIMODO (PAC08-0157-0668) project (Castilla-La Mancha Ministry of Education). Jesús Pardillo and Jose-Norberto Mazón are funded by the Spanish Ministry of Education (FPU grants AP2006-00332 and AP2005-1360).