Opinion Mining with Density Forests

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