Abstract
This paper presents an open cloud based platform for composition, execution, and sharing of interactive data mining workflows. It is based on the principles of service-oriented knowledge discovery, and features interactive scientific workflows. In contrast to comparable data mining platforms, our platform runs in all major Web browsers and platforms, including mobile devices. In terms of crowdsourcing, ClowdFlows provides researchers with an easy way to expose and share their work and results, as only an Internet connection and a Web browser are required to access the workflows from anywhere. Practitioners can use ClowdFlows to seamlessly integrate and join different implementations of algorithms, tools and Web services into a coherent workflow that can be executed in a cloud based application. ClowdFlows is also easily extensible during run-time by importing Web services and using them as new workflow components.
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Kranjc, J., Podpečan, V., Lavrač, N. (2012). ClowdFlows: A Cloud Based Scientific Workflow Platform. In: Flach, P.A., De Bie, T., Cristianini, N. (eds) Machine Learning and Knowledge Discovery in Databases. ECML PKDD 2012. Lecture Notes in Computer Science(), vol 7524. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33486-3_54
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DOI: https://doi.org/10.1007/978-3-642-33486-3_54
Publisher Name: Springer, Berlin, Heidelberg
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