Object-oriented application frameworks
Communications of the ACM
Software architecture in practice
Software architecture in practice
Design and use of software architectures: adopting and evolving a product-line approach
Design and use of software architectures: adopting and evolving a product-line approach
Component-based data mining frameworks
Communications of the ACM
Smart Archive: a Component-based Data Mining Application Framework
ISDA '05 Proceedings of the 5th International Conference on Intelligent Systems Design and Applications
YALE: rapid prototyping for complex data mining tasks
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Data mining applications for diverse industrial application domains with smart archive
SE '08 Proceedings of the IASTED International Conference on Software Engineering
Improving the classification accuracy of streaming data using SAX similarity features
Pattern Recognition Letters
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In this paper a new architecture for a variety of data mining tasks is introduced. The Device-Based Software Architecture (DBSA) is a highly portable and generic data mining software framework where processing tasks are modeled as components linked together to form a data mining application. The name of the architecture comes from the analogy that each processing task in the framework can be thought of as a device. The framework handles all the devices in the same manner, regardless of whether they have a counterpart in the real world or whether they are just logical devices inside the framework. The DBSA offers many reusable devices, ready to be included in applications, and the application programmer can easily code new devices for the architecture. The framework is bundled with connections to several widely used external tools and languages, making prototyping new applications easy and fast. In the paper we compare DBSA to existing data mining frameworks, review its design and present a case study application implemented with the framework. The paper shows that the DBSA can act as a base for diverse data mining applications.