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dc.contributor.authorWang, Xuanen_US
dc.date.accessioned2010-05-19T10:03:29Z
dc.date.available2012-02-24T10:03:42Z
dc.date.issued2010-05-04en_US
dc.identifier.urihttps://digital.library.txstate.edu/handle/10877/2597
dc.descriptionReport Number TXSTATE-CS-TR-2010-24.en_US
dc.description.abstractCloud computing has gained an increasing popularity over the years for its great potentials. It is a logical and forward-thinking solution for addressing key business demands. Cloud computing truly represents what enterprise IT always needs: a way to increase capacity or add capabilities on the fly without investing in new infrastructure, training new personnel, or licensing new software. Cloud computing encompasses any subscription-based or pay-per-use service that, in real time over the Internet, extends IT's existing capabilities. This study investigates how clustering algorithms in data mining can benefit from running in the "Cloud".en_US
dc.formatText
dc.format.extent14 pages
dc.format.medium1 file (.pdf)
dc.language.isoen_US
dc.subjectHadoopen_US
dc.subjectMapreduceen_US
dc.subjectAmazon EC2en_US
dc.subjectClusteringen_US
dc.subjectKmeansen_US
dc.subjectAlgorithmsen_US
dc.subjectCloud computingen_US
dc.subjectFrameworken_US
dc.subjectClustering algorithmsen_US
dc.subjectData miningen_US
dc.subject.classificationComputer Sciencesen_US
dc.titleClustering in the Cloud: Clustring Algorithms to Hadoop Map/Reduce Frameworken_US
txstate.documenttypeTechnical Report
txstate.departmentComputer Science


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