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Keeping in consideration the high demand for clustering, this paper focuseson understanding and implementing K-means clustering using two differentsimilarity measures. We have tried to cluster the documents using two differentmeasures rather than clustering it with Euclidean distance. Also a comparisonis drawn based on accuracy of clustering between fuzzy and cosine similaritymeasure. The start time and end time parameters for formation of clusters areused in deciding optimum similarity measure.

Comparison Clustering using Cosine and Fuzzy set based Similarity Measures of Text Documents