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A Survey Report on Text Classification with Different Term Weighing Methods and Comparison between Classification Algorithms
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 75 - Number 7 |
| Year of Publication: 2013 |
| Authors: Anuradha Patra, Divakar Singh |
10.5120/13122-0472
|
Anuradha Patra, Divakar Singh . A Survey Report on Text Classification with Different Term Weighing Methods and Comparison between Classification Algorithms. International Journal of Computer Applications. 75, 7 ( August 2013), 14-18. DOI=10.5120/13122-0472
Abstract
Text classification approach gaining more importance because of the accessibility of large number of electronic documents from a variety of resource. Text categorization is the task of assigning predefined categories to documents. It is the method of finding interesting regularities in large textual, where interesting means non trivial, hidden, previously unknown and potentially useful. The goal of text mining is to enable users to extract information from textual resource and deals with operation such as retrieval, classification, clustering, data mining, natural language preprocessing and machine learning techniques together to classify different pattern. In text classification, term weighting methods design appropriate weights to the given terms to improve the text classification performance. This paper surveys of text classification, process of text classification different term weighing methods and comparisons between different classification algorithms.
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