Cross domain sentiment classification of Thai reviews using co-train model

Warakorn Boonpetch; Orachat Chitsobhuk

doi:10.1117/12.2559609

31 December 2019 Cross domain sentiment classification of Thai reviews using co-train model

Proceedings Volume 11384, Eleventh International Conference on Signal Processing Systems; 113840V (2019) https://doi.org/10.1117/12.2559609
Event: Eleventh International Conference on Signal Processing Systems, 2019, Chengdu, China

Abstract

Online reviews are significant sources of information, which is useful for supporting customer and entrepreneur decision in terms of product and service satisfaction analysis. Online reviews containing feedback from various domains makes it difficult to analyze and classify all comments at once. The proposed technique analyses the cross-domain Thai review data using a co-train machine learning model. The co-train model consists of multiple single domain specific models followed by refinement analysis for the final sentiment classification. This allows for full flexibility in training of each individual domain, which can lessen the limitation on training complexity due to simple training on single domain. The experiments have been conducted on Wongnai restaurant domain and IMDB movie domain data. Our co-train model can achieve the highest average accuracy of 86.10 percent for cross-domain sentiment classification with approximately 38 seconds processing time.

Citation Download Citation

Warakorn Boonpetch and Orachat Chitsobhuk "Cross domain sentiment classification of Thai reviews using co-train model", Proc. SPIE 11384, Eleventh International Conference on Signal Processing Systems, 113840V (31 December 2019); https://doi.org/10.1117/12.2559609

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