Augmenting Rapid Clustering Method for Social Network Analysis

Presently, in the data mining scenario clustering of large dataset is one of the very important techniques widely applied to many applications including social network analysis. Applying more specific pre-processing method to prepare the data for clustering algorithms is considered to be a significant step for generating meaningful segments. In this paper we propose an innovative clustering technique called the Rapid Clustering Method (RCM), which uses Subtractive Clustering combined with Fuzzy C-Means clustering along with a histogram sampling technique to provide quick and effective results for large sized datasets. Rapid Clustering Method can be used to cluster the dataset and analyze the characteristics in a social network. It can also be used to enhance the cross-selling practices using quantitative association rule mining.