JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE) ›› 2015, Vol. 50 ›› Issue (11): 67-73.doi: 10.6040/j.issn.1671-9352.0.2015.082

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Product reviews sentiment classification in Micro-blog based on cascaded conditional random field

HE Yan-xiang1,2, LIU Jian-bo1,2, SUN Song-tao1,2, WEN Wei-dong1,2   

  1. 1. Computer School of Wuhan University, Wuhan 430072, Hubei, China;
    2. State Key Laboratory of Software Engineering, Wuhan 430072, Hubei, China
  • Received:2015-02-12 Revised:2015-11-11 Online:2015-11-20 Published:2015-12-09

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Abstract: Product reviews are subjective comments submitted by customers. Nowadays, product reviews are in the form of Micro-blog text which is typically very short but with varied structures. We proposed a novel sentiment classification method for product reviews from Micro-blog based on cascaded Conditional Random Field(CRF). First, review sentences were divided into a number of clauses based on the theory of clausal pivot. Then, features of the Chinese clause sequences were exploited to train a coarse-grained CRF sentiment classification model. Meanwhile, features of the Chinese character sequences within clauses were exploited to train a fine-grained CRF sentiment classification model. The experimental evaluation shows that the proposed method is better than the state-of-the-art ones.

Key words: Micro-blog, sentiment analysis, theory of clausal pivot, CRF

CLC Number: 

  • TP391
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