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Title: Efficient K-Means Clustering Algorithm Using Complexity Reduction Approach

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Title:
Efficient K-Means Clustering Algorithm Using Complexity Reduction Approach
Author Name:
Sudesh Kumar, Nancy
Abstract:
This paper introduces the concept of Data mining with K-Mean Clustering. The Data mining is the main object that finds the useful patterns among the large amount of data. Today most of the work is done on Internet. So, mining of data becomes essential thing for easy searching of data. Mining of data is done using multiple clustering techniques. Cluster Analysis seeks to identify homogeneous groups of objects based on the values of their attributes. The performance of clustering depends upon centroids selection and frequency of nearest data. The existing K-Means technique is complex in terms of time and calculation. This paper proposed the modified approach of K-Means clustering and algorithm has been designed. The entire data will be divided in number of groups based on the required cluster and highest frequency group will be considered. The fast clustering process will reduce the system resources and provides the efficient technique to generate the clusters.
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