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With large sets of text documents increasing rapidly, being able to efficiently utilize this vast volume of new information and service resource presents challenges to computational scientists. Text documents are usually modeled as a term-document matrix which has high dimensional and space vectors. To reduce the high dimensions, one of the various dimensionality reduction methods, concept decomposition, has been developed by some researchers. This method is based on document clusteringdoi:10.5120/17406-7991 fatcat:4jp4opwtzbg7tah3cwepkngufq