Volume 20 No 16 (2022)
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Cluster Analysis for Cloud Data through KMeans Technique
Banshidhar Chaudhary and Prof. VipinSaxena
Abstract
In the current scenario, many of organisations are transferring large databases over the cloud and for which public/private clouds are available. The sizes of the database are increasing in an exponential manner and due to heavy file size of video files, it is necessary to store large database over the cloud. In the present work, a concept of data mining is used to create the different kinds of clusters and further K-means method is applied for analysis of clusters to find out the duplicate pattern in the database, which may in the forms of duplicate files or duplicate folders. A sample database of credit cards is considered for analysis purpose and computed results are obtained in the form of tables and graphs. Validations are also performed by performing the various feasible queries. After setting the duplicate pattern in database, the same are stored inside the clusters and removed by performing feasible queries
Keywords
Sample Database, Cloud Data, Hidden Pattern, Cluster Analysis, and K-mean Technique
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