The week's pick
Reseach Article
An Enhanced Data Mining For Text Clustering
| International Conference on Recent Trends in Engineering and Technology 2013 |
| Foundation of Computer Science USA |
| ICRTET - Number 2 |
| May 2013 |
| Authors: Rupali D. Tajanpure, D. B. Kshirsagar |
| d87d9d27-31f7-4b6e-98b1-3357c893f41a |
Rupali D. Tajanpure, D. B. Kshirsagar . An Enhanced Data Mining For Text Clustering. International Conference on Recent Trends in Engineering and Technology 2013. ICRTET, 2 (May 2013), 19-23.
Abstract
Text mining is based on the statistical analysis of a term, either word or phrase. Statistical analysis of a term frequency captures the importance of the term within document only. Usually in text mining techniques the basic measures like term frequency of a term (word or phrase) is computed to compute the importance of the term in the document. But with statistical analysis, the original semantics of the term may not carry the exact meaning of the term. To overcome this problem, a new framework has been introduced which relies on concept based model approach. The proposed model can efficiently find significant matching and related concepts between documents according to concept based approaches.
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