University Visvesvaraya College of Engineering, UVCETo: Author

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CSTZ7U17
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Text mining, also known as Intelligent Text Analysis is an important research area. It is very difficult to focus on the most appropriate information due to the high dimensionality of data. Feature Extraction is one of the important techniques in data reduction to discover the most important features. Proce-ssing massive amount of data stored in a unstructured form is a challenging task. Several pre-processing methods and algo-rithms are needed to extract useful features from huge amount of data. The survey covers different text summarization, classi-fication, clustering methods to discover useful features and also discovering query facets which are multiple groups of words or phrases that explain and summarize the content covered by a query thereby reducing time taken by the user.
Ramya S, Venugopal R. 2017. "Feature Extraction and Duplicate Detection for Text Mining: A Survey". Global Journal of Computer Science and Technology, Global Journal of Computer Science and Technology - C: Software & Data Engineering GJCST-C Volume 16 (GJCST Volume 16 Issue C5).
Crossref Journal DOI 10.17406/gjcst
Print ISSN 0975-4350
e-ISSN 0975-4172
v1.2
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Total Score: 144
Country: India
Subject: Global Journal of Computer Science and Technology
Authors: Ramya R S, Venugopal K R, Iyengar S S, Patnaik L M (PhD/Dr. count: 0)
View Count (all-time): 475
Total Views (Real + Logic): 1859
Total Downloads (simulated): 149
Publish Date: 2016 01, Fri
Monthly Totals (Real + Logic):
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