Research on Sentiment Classification Algorithms on Online Review

المؤلفون المشاركون

Wang, Xiaoli
Yan, Ruixia
Xia, Zhijie
Xie, Yanxi
Song, Zukang

المصدر

Complexity

العدد

المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-6، 6ص.

الناشر

Hindawi Publishing Corporation

تاريخ النشر

2020-09-08

دولة النشر

مصر

عدد الصفحات

6

التخصصات الرئيسية

الفلسفة

الملخص EN

The product online review text contains a large number of opinions and emotions.

In order to identify the public’s emotional and tendentious information, we present reinforcement learning models in which sentiment classification algorithms of product online review corpus are discussed in this paper.

In order to explore the classification effect of different sentiment classification algorithms, we conducted a research on Naive Bayesian algorithm, support vector machine algorithm, and neural network algorithm and carried out some comparison using a concrete example.

The evaluation indexes and the three algorithms are compared in different lengths of sentence and word vector dimensions.

The results present that neural network algorithm is effective in the sentiment classification of product online review corpus.

نمط استشهاد جمعية علماء النفس الأمريكية (APA)

Yan, Ruixia& Xia, Zhijie& Xie, Yanxi& Wang, Xiaoli& Song, Zukang. 2020. Research on Sentiment Classification Algorithms on Online Review. Complexity،Vol. 2020, no. 2020, pp.1-6.
https://search.emarefa.net/detail/BIM-1142243

نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)

Yan, Ruixia…[et al.]. Research on Sentiment Classification Algorithms on Online Review. Complexity No. 2020 (2020), pp.1-6.
https://search.emarefa.net/detail/BIM-1142243

نمط استشهاد الجمعية الطبية الأمريكية (AMA)

Yan, Ruixia& Xia, Zhijie& Xie, Yanxi& Wang, Xiaoli& Song, Zukang. Research on Sentiment Classification Algorithms on Online Review. Complexity. 2020. Vol. 2020, no. 2020, pp.1-6.
https://search.emarefa.net/detail/BIM-1142243

نوع البيانات

مقالات

لغة النص

الإنجليزية

الملاحظات

Includes bibliographical references

رقم السجل

BIM-1142243