Abstract：We put forward an approach to recognizing sentiment polarity in Chinese reviews based on the shallow text structure that is represented by topic sentiment sentences. Considering the features of reviews, we identify the topic of a review using an n-gram matching approach. To extract topic sentiment sentences, we compute the semantic similarity of a candidate sentence and the ascertained topic, and meanwhile determine whether the sentence is subjective. A certain number of these sentences are selected as representatives according to their semantic similarity value with relation to the topic. The average value of the representative topic sentiment sentences is calculated and regarded as the sentiment polarity of a review. Experiment result shows that the proposed method is feasible and can achieve relatively high precision. Key wordsshallow text structure; topic sentiment sentence; review; sentiment orientation analysis; sentiment
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