Hesitant Distance Similarity Measures for Document Clustering

This paper presents new approach, Hesitant Distance Similarity Measures for Document Clustering. The proposed Hesitant Distance Similarity Measures approach is based on Fuzzy Hesitant Sets. In this paper we have used fifty Similarity Measures from f1 to f50. The steps, Document collection, Text Pre-processing, Feature Selection, Indexing, Clustering Process and Results Analysis are used. Twenty News group data sets [27] are used in the Experiments. The experimental results are evaluated using the Analytical SAS 9.0 Software. The Experimental Results show the proposed approach out performs.