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An Ensemble of Shallow and Deep Learning Algorithms for Vietnamese Sentiment Analysis

Nguyen, H.-Q. and Nguyen, Q.-U. (2019) An Ensemble of Shallow and Deep Learning Algorithms for Vietnamese Sentiment Analysis. In: 5th NAFOSTED Conference on Information and Computer Science, NICS 2018, 23 November 2018 through 24 November 2018.

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Abstract

Sentiment analysis also known as opinion mining refers to the use of natural language processing to systematically identify and categorize opinions expressed in a piece of text. Recently, deep learning with ensemble techniques has achieved state of the art results in sentiment analysis. However, this approach has not been studied for Vietnamese corpus. In this paper, we propose an ensemble method by combining traditional (shallow) and deep learning algorithms. We tested our method on three Vietnamese sentiment datasets. The Experimental results showed that these approaches improve the accuracy of sentiment classification when compared to both individual deep and shallow algorithms. © 2018 IEEE.

Item Type: Conference or Workshop Item (Paper)
Divisions: Faculties > Faculty of Information Technology
Identification Number: 10.1109/NICS.2018.8606880
Uncontrolled Keywords: Data mining; Deep learning; Sentiment analysis; Ensemble learning; Ensemble methods; Ensemble techniques; NAtural language processing; Opinion mining; Sentiment classification; State of the art; Vietnamese; Learning algorithms
Additional Information: Conference code: 144343. Language of original document: English.
URI: http://eprints.lqdtu.edu.vn/id/eprint/9402

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