Research Article
A Vietnamese Sentiment Analysis System Based on Multiple Classifiers with Enhancing Lexicon Features
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@INPROCEEDINGS{10.1007/978-3-030-30149-1_20, author={Bich-Tuyen Nguyen-Thi and Huu-Thanh Duong}, title={A Vietnamese Sentiment Analysis System Based on Multiple Classifiers with Enhancing Lexicon Features}, proceedings={Industrial Networks and Intelligent Systems. 5th EAI International Conference, INISCOM 2019, Ho Chi Minh City, Vietnam, August 19, 2019, Proceedings}, proceedings_a={INISCOM}, year={2019}, month={9}, keywords={Machine learning Text mining Natural language processing Sentiment analysis User behavior}, doi={10.1007/978-3-030-30149-1_20} }- Bich-Tuyen Nguyen-Thi
Huu-Thanh Duong
Year: 2019
A Vietnamese Sentiment Analysis System Based on Multiple Classifiers with Enhancing Lexicon Features
INISCOM
Springer
DOI: 10.1007/978-3-030-30149-1_20
Abstract
Today, a customer is easy to express his opinions about a bought products thanks to accelerated development of social networks and ecommerce websites. These opinions are very useful indicators to evaluate the degree of the customers’ real satisfaction. From that, the traders will emerge the strategies and predict the trends to get the directions for their products and businesses in the future. In this paper, we have built a dataset and executed many experiments based on the multiple classifiers with complementing lexicon features to increase the accuracy of sentiment polarities. The experimental section shows good results and proves our approach is reasonable.
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