On the Feature Selection and Classification Based on Information Gain for Document Sentiment Analysis

المؤلفون المشاركون

Pratiwi, Asriyanti Indah
Adiwijaya, Asriyanti Indah

المصدر

Applied Computational Intelligence and Soft Computing

العدد

المجلد 2018، العدد 2018 (31 ديسمبر/كانون الأول 2018)، ص ص. 1-5، 5ص.

الناشر

Hindawi Publishing Corporation

تاريخ النشر

2018-02-19

دولة النشر

مصر

عدد الصفحات

5

التخصصات الرئيسية

تكنولوجيا المعلومات وعلم الحاسوب

الملخص EN

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.

نمط استشهاد جمعية علماء النفس الأمريكية (APA)

Pratiwi, Asriyanti Indah& Adiwijaya, Asriyanti Indah. 2018. On the Feature Selection and Classification Based on Information Gain for Document Sentiment Analysis. Applied Computational Intelligence and Soft Computing،Vol. 2018, no. 2018, pp.1-5.
https://search.emarefa.net/detail/BIM-1117037

نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)

Pratiwi, Asriyanti Indah& Adiwijaya, Asriyanti Indah. On the Feature Selection and Classification Based on Information Gain for Document Sentiment Analysis. Applied Computational Intelligence and Soft Computing No. 2018 (2018), pp.1-5.
https://search.emarefa.net/detail/BIM-1117037

نمط استشهاد الجمعية الطبية الأمريكية (AMA)

Pratiwi, Asriyanti Indah& Adiwijaya, Asriyanti Indah. On the Feature Selection and Classification Based on Information Gain for Document Sentiment Analysis. Applied Computational Intelligence and Soft Computing. 2018. Vol. 2018, no. 2018, pp.1-5.
https://search.emarefa.net/detail/BIM-1117037

نوع البيانات

مقالات

لغة النص

الإنجليزية

الملاحظات

Includes bibliographical references

رقم السجل

BIM-1117037