Extraction of sentiment topic sentences of Chinese texts
中文文本情感主题句分析与提取研究

This paper proposed a method of extracting sentiment topic sentences. Firstly semantic concepts of a text were evaluated in order to determine which concepts were related to the topic of a text. And the concepts related to the topic were regarded as topic concepts. Sentences including one or more topic concepts were defined as candidate sentences. Significance of every candidate sentences was calculated in order to which ones were topic sentences in the text. Conditional random field model was adopted and two kinds of feature were used in the model training, and one feature was polarity of sentiment and the other feature was transferring words. This approach excluded sentences that were not related to the topic of the text, and eliminated the influence brought by these sentences. Therefore, precision of sentiment analysis is effectively improved.