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IAJIT
2016

Mahalanobis distance-the ultimate measure for sentiment analysis

3 years 6 months ago
Mahalanobis distance-the ultimate measure for sentiment analysis
: In this paper, Mahalanobis Distance (MD) has been proposed as a measure to classify the sentiment expressed in a review document as either positive or negative. A new method for representing the text documents using Representative Terms (RT) has been used. The new way of representing text documents using few representative dimensions is relatively a new concept, which is successfully demonstrated in this paper. The MD based classifier performed with 70.8% of accuracy for the experiments carried out using the benchmark dataset containing 25000 movie reviews. The hybrid of MD based Classifier (MDC) and Multi Layer Perceptron (MLP) resulted in a 98.8% of classification accuracy, which is the highest ever reported accuracy for a dataset containing 25000 reviews.
Valarmathi Balasubramanian, Srinivasa Gupta Nagara
Added 04 Apr 2016
Updated 04 Apr 2016
Type Journal
Year 2016
Where IAJIT
Authors Valarmathi Balasubramanian, Srinivasa Gupta Nagarajan, Palanisamy Veerappagoundar
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