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An Approach to Improve Quality of Document Clustering by Word Set Based Documenting Clustering Algorithm


Affiliations
1 Department of Computer Science and Engineering, Suresh Gyan Vihar University, Jaipur, India
 

This paper presents a technique to improve the quality of Document Clustering based on Word Set Concept. The proposed Technique WDC (word set based document clustering), a clustering algorithm work with to obtain clustering of comparable quality significantly more efficiently more than the state of the art text clustering algorithm. The proposed WDC algorithms utilize the semantic relation ship between words to create concepts. The Word sets based Document Clustering (WDC) obtains clustering of comparable quality significantly more efficiently than state-of-art approach is efficient and give more accurate clustering result than the other methods.

Keywords

Document Clustering, Frequent Concept, Word Set.
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  • An Approach to Improve Quality of Document Clustering by Word Set Based Documenting Clustering Algorithm

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Authors

Sandeep Sharma
Department of Computer Science and Engineering, Suresh Gyan Vihar University, Jaipur, India
Ruchi Dave
Department of Computer Science and Engineering, Suresh Gyan Vihar University, Jaipur, India
Naveen Hemrajani
Department of Computer Science and Engineering, Suresh Gyan Vihar University, Jaipur, India

Abstract


This paper presents a technique to improve the quality of Document Clustering based on Word Set Concept. The proposed Technique WDC (word set based document clustering), a clustering algorithm work with to obtain clustering of comparable quality significantly more efficiently more than the state of the art text clustering algorithm. The proposed WDC algorithms utilize the semantic relation ship between words to create concepts. The Word sets based Document Clustering (WDC) obtains clustering of comparable quality significantly more efficiently than state-of-art approach is efficient and give more accurate clustering result than the other methods.

Keywords


Document Clustering, Frequent Concept, Word Set.