Research Article
Opinion Mining with Density Forests
@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
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
Copyright © 2023 Author et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution license, which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.
