The manual reading of all the product reviews to find a satisfying item is not only labor-intensive, but also tedious for the consumers. In this paper, we propose a feature-opinion mining approach to automatically summarize the reviews, which is based on dependency parsing. Specifically, in our approach we first utilize a regression model to generate sentiment word, including phrase and its sentiment weight, and then we extract the feature based on the dependency relationship between feature word and sentiment word, finally we assign a score to the feature according to the dependency relationship. The experimental results demonstrate that our approach can effectively mine the feature-opinion from reviews.
