On the Feature Selection and Classification Based on Information Gain for Document Sentiment Analysis. (19th February 2018)

• Record Type: Journal Article
• Authors: Pratiwi, Asriyanti Indah; Adiwijaya,
• Other Names: Zunino Rodolfo Academic Editor.
• Is Part Of: Applied computational intelligence and soft computing. Volume 2018(2018)
• Publication Date: 2018-02-19
• Subjects: Computational intelligence -- Periodicals; Soft computing -- Periodicals; 006.305
• DOI: 10.1155/2018/1407817
• Languages: English
• ISSNs: 1687-9724

Abstract

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.