Open AccessResearch of Clustering Algorithms using Enhanced Feature Selection
Author(s) -
Venkata Nagaraju Thatha,
A. Sudhir Babu,
D. Haritha
Publication year - 2019
Publication title -
international journal of engineering and advanced technology
Language(s) - English
Resource type - Journals
ISSN - 2249-8958
DOI - 10.35940/ijeat.b5115.129219
Subject(s) - automatic summarization , cluster analysis , computer science , feature selection , selection (genetic algorithm) , focus (optics) , task (project management) , variety (cybernetics) , data mining , feature extraction , information retrieval , relation (database) , artificial intelligence , feature (linguistics) , pattern recognition (psychology) , engineering , linguistics , philosophy , physics , systems engineering , optics
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.