Affiliation:
1. Telkom University, Telekomunikasi Street No. 1, Bandung 40257, Indonesia
Abstract
Sentiment analysis in a movie review is the needs of today lifestyle. Unfortunately, enormous features make the sentiment of analysis slow and less sensitive. Finding the optimum feature selection and classification is still a challenge. In order to handle an enormous number of features and provide better sentiment classification, an information-based feature selection and classification are proposed. The proposed method reduces more than 90% unnecessary features while the proposed classification scheme achieves 96% accuracy of sentiment classification. From the experimental results, it can be concluded that the combination of proposed feature selection and classification achieves the best performance so far.
Subject
Artificial Intelligence,Computer Networks and Communications,Computer Science Applications,Civil and Structural Engineering,Computational Mechanics
Cited by
36 articles.
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