Context-Aware Systems and Applications. 10th EAI International Conference, ICCASA 2021, Virtual Event, October 28–29, 2021, Proceedings

Research Article

Ensemble Learning for Mining Opinions on Food Reviews

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  • @INPROCEEDINGS{10.1007/978-3-030-93179-7_5,
    author={Phuc Quang Tran and Hai Thanh Nguyen and Hanh My Thi Le and Hiep Xuan Huynh},
    title={Ensemble Learning for Mining Opinions on Food Reviews},
    proceedings={Context-Aware Systems and Applications. 10th EAI International Conference, ICCASA 2021, Virtual Event,  October 28--29, 2021, Proceedings},
    proceedings_a={ICCASA},
    year={2022},
    month={1},
    keywords={Opinion mining Opinion ensemble learning Food reviews},
    doi={10.1007/978-3-030-93179-7_5}
}
  • Phuc Quang Tran
    Hai Thanh Nguyen
    Hanh My Thi Le
    Hiep Xuan Huynh
    Year: 2022
    Ensemble Learning for Mining Opinions on Food Reviews
    ICCASA
    Springer
    DOI: 10.1007/978-3-030-93179-7_5
Phuc Quang Tran1, Hai Thanh Nguyen2, Hanh My Thi Le3, Hiep Xuan Huynh2,*
  • 1: Faculty of Foreign Language and Informatics
  • 2: College of Information and Communication Technology
  • 3: Faculty of Information Technology
*Contact email: hxhiep@ctu.edu.vn

Abstract

This paper proposes an ensemble learning model for opinion mining on food reviews. The proposed model is built on an ensemble of decision trees called Random classification forest. This model performs the task of classifying sentiment about food as positive, negative, or neutral. The ensemble learning model was evaluated on two scenarios, which we built based on important features of the reviews. The experimental results on the food reviews data set have shown the effectiveness of the proposed model.

Keywords
Opinion mining Opinion ensemble learning Food reviews
Published
2022-01-06
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-030-93179-7_5
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