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Implementation of K MEAN Partitioning Method in Educated Collective System

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dc.contributor.author Htun, Thida
dc.date.accessioned 2019-07-31T04:01:41Z
dc.date.available 2019-07-31T04:01:41Z
dc.date.issued 2009-12-30
dc.identifier.uri http://onlineresource.ucsy.edu.mm/handle/123456789/1489
dc.description.abstract Clustering is a highly popular and widely used tool for identifying or constructing data based market pieces. In recent years, there have been growing interests in developing effective methods for searching large database based on multi-dimensional contents. Consequently, this paper intends to build up a Public Figures Civilizing (PFC) system with a common partitioning method, k-means. Most of universities make all of their duties with manual system. So this system implement computerize system for them and especially for issuing exam result. Furthermore, this information should be made accessible from consistent provision, because each developing country should promote the social standard with knowledgeable individual. For this reason, the proposed system can support the statistics of the information with two components: Client Visible Frame (CVF) module and K-means Clustering Execution (KCE) module. This paper temporarily describes the chief occupation of these two modules as a reasonable behavior. en_US
dc.language.iso en en_US
dc.publisher Fourth Local Conference on Parallel and Soft Computing en_US
dc.title Implementation of K MEAN Partitioning Method in Educated Collective System en_US
dc.type Article en_US


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