Model-driven data mining engineering: from solution-driven implementations to 'composable' conceptual data mining models
Alfredo Cuzzocrea,
Jose-Norberto Mazon,
Juan Trujillo and
Jose Zubcoff
International Journal of Data Mining, Modelling and Management, 2011, vol. 3, issue 3, 217-251
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. (search for similar items in EconPapers)
Date: 2011
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Persistent link: https://EconPapers.repec.org/RePEc:ids:ijdmmm:v:3:y:2011:i:3:p:217-251
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