NDLI: A Cloud Framework for Parameter Sweeping Data Mining Applications

Content Provider	IEEE Xplore Digital Library
Author	Marozzo, F. Talia, D. Trunfio, P.
Copyright Year	2011
Abstract	Data mining techniques are used in many application areas to extract useful knowledge from large datasets. Very often, parameter sweeping is used in data mining applications to explore the effects produced on the data analysis result by different values of the algorithm parameters. Parameter sweeping applications can be highly computing demanding, since the number of single tasks to be executed increases with the number of swept parameters and the range of their values. Cloud technologies can be effectively exploited to provide end-users with the computing and storage resources, and the execution mechanisms needed to efficiently run this class of applications. In this paper, we present a Data Mining Cloud App framework that supports the execution of parameter sweeping data mining applications on a Cloud. The framework has been implemented using the Windows Azure platform, and evaluated through a set of parameter sweeping clustering and classification applications. The experimental results demonstrate the effectiveness of the proposed framework, as well as the scalability that can be achieved through the parallel execution of parameter sweeping applications on a pool of virtual servers.
Starting Page	367
Ending Page	374
File Size	921682
Page Count	8
File Format	PDF
ISBN	9781467300902
DOI	10.1109/CloudCom.2011.56
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-11-29
Publisher Place	Greece
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Cloud computing Clustering algorithms User interfaces Data mining Servers Parameter sweeping Monitoring
Content Type	Text
Resource Type	Article

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