Opinion Mining with Density Forests

Authors

DOI:

https://doi.org/10.4108/eetcasa.v9i1.3272

Keywords:

DBSCAN Clustering, Density Forests, Opinion mining, Hotel Reviews, Restaurant Reviews

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

References

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Published

10-07-2023

How to Cite

1.
Tran PQ, Ha DNL, Le HTM, Huynh HX. Opinion Mining with Density Forests. EAI Endorsed Trans Context Aware Syst App [Internet]. 2023 Jul. 10 [cited 2024 Apr. 25];9. Available from: https://publications.eai.eu/index.php/casa/article/view/3272