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| The HGSD Method for Consumption Sentiment Classification |
| LIN Ming-Ming1, QIU Yun-Fei1, SHAO Liang-Shan2 |
1.School of Software, Liaoning Technical University, Huludao 125100
2.System Engineering Institute, Liaoning Technical University, Huludao 125100 |
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Abstract Aiming at the sentiment classification for Chinese consumption comments, a sentiment classification method combining dictionary semantic concept and context semanteme is proposed. Firstly, a method of extracting benchmark words set of different domains is put forword. Then, the sentiment words are extracted through the similarity of HowNet based on the unigram model. Finally, HowNet and Google similarity distance (HGSD) combining the HowNet similarity and the Google similarity distance is presented to classify the sentences, which reflects the original meaning of the word and the meaning in the context. Experiments of consumption comments on books, computers and hotels show the higher F-measure of the proposed method, and meanwhile the contrast experiment shows the effectiveness of the proposed algorithm.
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Received: 15 January 2014
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2015, Vol. 28 
