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Text Mining and Clustering Analysis


Shobha S. Raskar, D. M. Thakore


Vol. 11  No. 6  pp. 203-207


Cluster analysis is required in text mining for grouping objects. Cluster analysis consists of different algorithms and methods for grouping objects of similar kinds into respective categories. Cluster analysis is exploratory data analysis tool which aims at sorting different objects into groups in a way that the degree of association between two objects is maximal, if they belong to same group and minimal otherwise. It can be used to discover structure in data without providing an explanation or interpretation. Cluster analysis simply discover structure in data without explaining, why they exist. Aim of text mining, text clustering is to divide collection of text document into different category group should be of little similarity. Cluster is comprised of number of similar object collected or grouped together. Cluster analysis is tool for exploring structure of data clustering is subjective or problem dependent. Basic objective in cluster analysis is to discover natural grouping of items. Quantitative scale is developing which measure association between object, these scales are referred as similarity measure.


Clustering, K-mean, Expectation Maximization(EM), Distance measure