Curtailment of Clustering Using SOQ

Provided by: Iosrjournals
Topic: Data Management
Format: PDF
In this paper, the authors proposed about self-organizing queue based clustering and its algorithms. Self-organizing clustering is more useful compared to spectral clustering. The draw-backs of graph clustering has been overcome by spectral clustering i.e., similarity matrix of a set of data points or nodes, this problem is commonly referred as k/a graph clustering. Experimental results have been clearly shown their dominance over other existing techniques such as spectral clustering, graph clustering and k-means algorithm. The experiment will be done by using Matlab software.

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