| The world is deluged with various kinds of data---scientific data, environmental data, financial data, and mathematical data. Manually analyzing, clustering, and summarizing this data is impossible because of the incredible increase in the amount data in this age of networks and information sharing. In this paper, an improved clustering algorithm for data clustering called K-MM (K-Means & Medoids) which combines two classical clustering algorithms, K-Means and K-Medoids is introduced. This paper also investigates the fundamentals of data mining and current research on clustering algorithms in data mining.;Key words: Clustering, K-MM, K-Means, K-Medoids... |
