Hesitant Distance Similarity Measures for Document Clustering

Author

Sahu, Neeraj ; Thakur, G.S.

Author_Institution

Singhania Univ., Pacheri Bari, India

fYear

2011

fDate

11-14 Dec. 2011

Firstpage

430

Lastpage

438

Abstract

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.

Keywords

fuzzy set theory; indexing; pattern clustering; text analysis; analytical SAS 9.0 software; document clustering; document collection; feature selection; fuzzy hesitant set; hesitant distance similarity measure; indexing; result analysis; text preprocessing; Accuracy; Clustering algorithms; Clustering methods; Communications technology; Euclidean distance; Hamming distance; Weight measurement; Clustering; Distance measure; Hesitant fuzzy set; Similarity measure;

fLanguage

English

Publisher

ieee

Conference_Titel

Information and Communication Technologies (WICT), 2011 World Congress on

Conference_Location

Mumbai

Print_ISBN

978-1-4673-0127-5

Type

conf

DOI

10.1109/WICT.2011.6141284

Filename

6141284