文章基本信息

标题：On the Feature Selection and Classification Based on Information Gain for Document Sentiment Analysis
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作者：Asriyanti Indah Pratiwi ; Adiwijaya
期刊名称：Applied Computational Intelligence and Soft Computing
印刷版ISSN：1687-9724
电子版ISSN：1687-9732
出版年度：2018
卷号：2018
DOI：10.1155/2018/1407817
出版社：Hindawi Publishing Corporation
摘要：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.