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A Survey on Clustering Algorithms


Affiliations
1 Department of Computer Applications, Sri Ramakrishna Institute of Technology, Coimbatore, India
2 Department of Computer Science, Sri Ramakrishna Arts College for Women, Coimbatore, India
     

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Clustering is a widely used technique to find interesting patterns dwelling in the dataset that remain unknown. In general, clustering is a method of dividing the data into groups of similar objects. One of significant research areas in data mining is to develop methods to modernize knowledge by using the existing knowledge, since it can generally augment mining efficiency,especially for very bulky database. Data mining uncovers hidden,previously unknown, and potentially useful information from large amounts of data. This paper presents a general survey of various clustering algorithms. In addition, the paper also describes the efficiency of Self-Organized Map (SOM) algorithm in enhancing the mixed data clustering.


Keywords

Data Clustering, Data Mining, Mixed Data Clustering, Self-Organized Map Algorithm.
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  • A Survey on Clustering Algorithms

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Authors

D. Hari Prasad
Department of Computer Applications, Sri Ramakrishna Institute of Technology, Coimbatore, India
M. Punithavalli
Department of Computer Science, Sri Ramakrishna Arts College for Women, Coimbatore, India

Abstract


Clustering is a widely used technique to find interesting patterns dwelling in the dataset that remain unknown. In general, clustering is a method of dividing the data into groups of similar objects. One of significant research areas in data mining is to develop methods to modernize knowledge by using the existing knowledge, since it can generally augment mining efficiency,especially for very bulky database. Data mining uncovers hidden,previously unknown, and potentially useful information from large amounts of data. This paper presents a general survey of various clustering algorithms. In addition, the paper also describes the efficiency of Self-Organized Map (SOM) algorithm in enhancing the mixed data clustering.


Keywords


Data Clustering, Data Mining, Mixed Data Clustering, Self-Organized Map Algorithm.