Conventional programming models were designed to be used by expert programmers for programming for largescale multiprocessors, distributed computational clusters, or specialized p...
The deluge of available data for analysis demands the need to scale the performance of data mining implementations. With the current architectural trends, one of the major challen...
Spectral clustering is a simple yet powerful method for finding structure in data using spectral properties of an associated pairwise similarity matrix. This paper provides new in...
Although many methods of refining initialization have appeared, the sensitivity of K-Means to initial centers is still an obstacle in applications. In this paper, we investigate a...
In this paper a fuzzy quantization dequantization criterion is used to propose an evaluation technique to determine the appropriate clustering algorithm suitable for a particular ...