MPRK algorithm for clustering the large text datasets

Text Document clustering is changing the massive collections of text documents into a lesser amount of suitable clusters. While numerous clustering approaches have been projected in the last few decades, the partitioned clustering algorithms are stated performing well on document clustering based on the reviewed papers. In this research, Modified Parallel Rough K-means (MPRK) algorithm is proposed for clustering the text document and it is evaluated on datasets and the results are compared to benchmark algorithms K-means and DPPSOK-means. The experimental analysis shows the proposed algorithm produces efficient result compared to the existing algorithms.

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