Clustering in the Cloud: Clustring Algorithms to Hadoop Map/Reduce Framework
dc.contributor.author | Wang, Xuan | |
dc.date.accessioned | 2010-05-19T10:03:29Z | |
dc.date.available | 2012-02-24T10:03:42Z | |
dc.date.issued | 2010-05 | |
dc.description.abstract | Cloud 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". | |
dc.description.department | Computer Science | |
dc.format | Text | |
dc.format.extent | 14 pages | |
dc.format.medium | 1 file (.pdf) | |
dc.identifier.citation | Wang, X. (2010). Clustering in the cloud (Report No. TXSTATE-CS-TR-2010-24). Texas State University-San Marcos, Department of Computer Science. | |
dc.identifier.uri | https://hdl.handle.net/10877/2597 | |
dc.language.iso | en | |
dc.subject | hadoop | |
dc.subject | mapreduce | |
dc.subject | Amazon EC2 | |
dc.subject | clustering | |
dc.subject | Kmeans | |
dc.subject | algorithms | |
dc.subject | cloud computing | |
dc.subject | framework | |
dc.subject | clustering algorithms | |
dc.subject | data mining | |
dc.title | Clustering in the Cloud: Clustring Algorithms to Hadoop Map/Reduce Framework | |
dc.type | Report |
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