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An effective grid clustering algorithm based on least clustering cell and its application

Authors: null Xianying Huang; null Sen Wang;

An effective grid clustering algorithm based on least clustering cell and its application

Abstract

The basic concept of clustering and its correlating research work is firstly present, a new algorithm based on least clustering cell (LCC) is proposed and analyzed which concerns the advantages and disadvantage of k-means and grid clustering algorithm. This algorithm is efficient in dealing with huge amounts of data and can make paralleled processing, which is proved to be correct, efficient and fast through application in customer relationship management. It overcomes the disadvantage of given the value k in k-means clustering algorithm and data dense in grid based clustering algorithm. Lastly the analysis and evaluation of the algorithm is given.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
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