Feature Extraction and Duplicate Detection for Text Mining: A Survey

Ramya R S
Ramya R S * §
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Venugopal K R
Venugopal K R
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§ University Visvesvaraya College of Engineering, UVCE

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Feature Extraction and Duplicate Detection for Text Mining: A Survey

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Abstract

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.

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No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

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How to Cite This Article

Ramya R S, Venugopal K R. 2017. "Feature Extraction and Duplicate Detection for Text Mining: A Survey". Global Journal of Computer Science and Technology - C: Software & Data Engineering GJCST-C Volume 16 (GJCST Volume 16 Issue C5).

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords
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C.2.1
C.2.4
H.2.8
  • Submission ReceivedDecember 12, 2015
  • Peer Review Double Blind
    Handling Editor
  • Accepted December 31, 2015
  • Published January 15, 2016
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v1.2

Issue date
January 27, 2017

Language
English
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Feature Extraction and Duplicate Detection for Text Mining: A Survey

Ramya S
Ramya S University Visvesvaraya College of Engineering, UVCE
Venugopal R
Venugopal R
  • Submission ReceivedDecember 12, 2015
  • Peer Review Double Blind
    Handling Editor
  • Accepted December 31, 2015
  • Published January 15, 2016