Cluster Analysis on Complex Structured and High Dimensional Data Objects Using K-Means and EM Algorithms

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Provided by: International Journal of Emerging Trends & Technology in Computer Science (IJETTCS)
Topic: Data Management
Format: PDF
Cluster analysis plays an outstanding role in data mining applications such as scientific data exploration, information retrieval, text mining, web analysis, marketing and many other application areas. Large number of clustering algorithms has been developed in a variety of domains for different types of applications. None of these clustering algorithms are suitable for all type of data, so finding out the characteristics of each partitioning clustering is important. This paper is to find out the performance of the partition clustering techniques in terms of complex data objects and comparative study of the cluster algorithm for corresponding data and proximity measure for specific objective function.
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