Data mining applications for diverse industrial application domains with smart archive

The increasing significance of data mining in many application domains of computational technology has resulted in a considerable body of work concerned with designing architectural models and collections of reusable software components to allow for more rapid deployment of data mining methods wherever they are deemed useful. Early work involved integrating machine learning algorithms and knowledge management features into class libraries; more recently the data mining research community has progressed towards application frameworks, which are based on the notion of a reusable high-level design rather than specific algorithms. Smart Archive provides such a design, fine-tuned for applications that process continuous measurements and make use of historical data. In this paper a pre-existing foundational framework is extended with a new layer of services and the overall system architecture established by the framework is examined. Two case studies drawn from diverse application domains—steelmaking and personal fitness products—are presented in order to validate the proposed design. The case studies show that Smart Archive is beneficial in integration, coding and testing tasks and suitable for both online and batch processing and for both localized and distributed applications.