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Feature Selection for Sentiment Analysis by using SVM
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 84 - Number 5 |
| Year of Publication: 2013 |
| Authors: Rohini S. Rahate, Emmanuel M |
10.5120/14573-2697
|
Rohini S. Rahate, Emmanuel M . Feature Selection for Sentiment Analysis by using SVM. International Journal of Computer Applications. 84, 5 ( December 2013), 24-32. DOI=10.5120/14573-2697
Abstract
Sentiment analysis depends on feature selection methods to approaches that use general statistical measures where features are selected on empirical evidence. Empirical evidence (research) is a way of gaining knowledge by means of direct and indirect observation or experience. there are new features selection schemes that use a content and syntax model that is used to automatically learn a set of features in a review document and removing the entities that are being reviewed from the subjective expression that describe those entities in terms of polarities.
References
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