Sentiment-Aspect Extraction based on Restricted Boltzmann Machines

Aspect extraction and sentiment analysis of reviews are both important tasks in opinion mining. We propose a novel sentiment and aspect extraction model based on Restricted Boltzmann Machines to jointly address these two tasks in an unsupervised setting. This model reflects the generation process of reviews by introducing a heterogeneous structure into the hidden layer and incorporating informative priors. Experiments show that our model outperforms previous state-of-the-art methods.

• Type: Journal
• Year: 2015
• Where: ACL
• Authors: Linlin Wang, Kang Liu, Zhu Cao, Jun Zhao 0001, Gerard de Melo
• Keywords: ACL 2015, Computational Linguistics