casa 24(1):

Research Article

Opinion Mining with Density Forests

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  • @ARTICLE{10.4108/eetcasa.v9i1.3272,
        author={Phuc Quang Tran and Dung Ngoc Le Ha and Hanh Thi My Le and Hiep Xuan Huynh},
        title={Opinion Mining with Density Forests},
        journal={EAI Endorsed Transactions on Context-aware Systems and Applications},
        volume={9},
        number={1},
        publisher={EAI},
        journal_a={CASA},
        year={2023},
        month={7},
        keywords={DBSCAN Clustering, Density Forests, Opinion mining, Hotel Reviews, Restaurant Reviews},
        doi={10.4108/eetcasa.v9i1.3272}
    }
    
  • Phuc Quang Tran
    Dung Ngoc Le Ha
    Hanh Thi My Le
    Hiep Xuan Huynh
    Year: 2023
    Opinion Mining with Density Forests
    CASA
    EAI
    DOI: 10.4108/eetcasa.v9i1.3272
Phuc Quang Tran1, Dung Ngoc Le Ha2, Hanh Thi My Le3, Hiep Xuan Huynh4,*
  • 1: People's Police College II
  • 2: Can Tho University if Technology
  • 3: University of Da Nang
  • 4: Can Tho University
*Contact email: hxhiep@ctu.edu.vn

Abstract

In this paper, we propose a new approach for opinion mining with density-based forests. We apply Density-Based Spatial Clustering of Applications with Noise (DBSCAN) to identify clusters of data points in a space of feature vectors that are important features of hotel and restaurant reviews, and then use the clusters to construct random forests to classify whether the opinions expressed about features in the reviews are positive or negative. Our experiment uses two standard datasets of hotel and restaurant reviews in two different scenarios. The experimental results show the effectiveness of our proposed