Research of Clustering Algorithms using Enhanced Feature Selection
Venkata Nagaraju Thatha1, A.Sudhir Babu2, D.Haritha3
1Venkata Nagaraju Thatha, Department of Computer Science & Engineering, JNTUK UNIVERSITY, Kakinada, Andhra Pradesh India.
2A. SudhirBabu, Department of Computer Science & Engineering, PVPSIT, Vijayawada, Andhra Pradesh India.
3D. Haritha, Department of Computer Science & Engineering, JNTUK UNIVERSITY, Kakinada, Andhra Pradesh India.
Manuscript received on November 22, 2019. | Revised Manuscript received on December 15, 2019. | Manuscript published on December 30, 2019. | PP: 4612-4615 | Volume-9 Issue-2, December, 2019. | Retrieval Number: B5115129219/2019©BEIESP | DOI: 10.35940/ijeat.B5115.129219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: -In Present situation, a huge quantity of data is recorded in variety of forms like text, image, video, and audio and is estimated to enhance in future. The major tasks related to text are entity extraction, information extraction, entity relation modeling, document summarization are performed by using text mining. This paper main focus is on document clustering, a sub task of text mining and to measure the performance of different clustering techniques. In this paper we are using an enhanced features selection for clustering of text documents to prove that it produces better results compared to traditional feature selection.
Keywords: Enhanced feature selection, text mining, clustering.