Jointly modeling aspects and opinions with a MaxEnt-LDA hybrid
Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing, page 56--65. Stroudsburg, PA, USA, Association for Computational Linguistics, (2010)Abstract
Discovering and summarizing opinions from online reviews is an important and challenging task. A commonly-adopted framework generates structured review summaries with aspects and opinions. Recently topic models have been used to identify meaningful review aspects, but existing topic models do not identify aspect-specific opinion words. In this paper, we propose a MaxEnt-LDA hybrid model to jointly discover both aspects and aspect-specific opinion words. We show that with a relatively small amount of training data, our model can effectively identify aspect and opinion words simultaneously. We also demonstrate the domain adaptability of our model.
