A comprehensive study on clustering approaches for big data mining

Technological advancement has enabled us to store and process huge amount of data items in a relatively much lesser span of time. The term "Big Data" simply refers to huge amount of data nowadays used frequently in industrial and research circles. The focus point here is not just the collection of data but careful analysis of the collected data so that meaningful results can be obtained. There are various ways of handling the huge incoming streams of data. One such way is clustering of data into compact units. This not only reduces the size of the data but also helps to utilize it in a more effective manner. This paper gives an overview and comparison of basic clustering algorithms, and suggests the suitability of clustering approaches for various sizes of data sets. A brief introduction to evolution of the clustering algorithms is also given.