A topic sentence-based instance transfer method for imbalanced sentiment classification of Chinese product reviews
作者：
Highlights：
• Proposed a topic sentence-based instance transfer method to process imbalanced Chinese product reviews.
• Introduced a rule and supervision learning hybrid method for identifying topic sentence of a product review.
• Incorporated feature set of the topic sentence to the feature space of sentiment classification.
• Used a SMOTE-based method to overcome feature space inconsistency between source dataset and target dataset.
• Result verified that our proposed methods helps SVM outperforms considering the ability of generalization.
摘要
•Proposed a topic sentence-based instance transfer method to process imbalanced Chinese product reviews.•Introduced a rule and supervision learning hybrid method for identifying topic sentence of a product review.•Incorporated feature set of the topic sentence to the feature space of sentiment classification.•Used a SMOTE-based method to overcome feature space inconsistency between source dataset and target dataset.•Result verified that our proposed methods helps SVM outperforms considering the ability of generalization.
论文关键词：Classification methods,Imbalanced sample classification,Instance transfer methods,Product reviews,Topic sentence analysis
论文评审过程：Received 28 February 2015, Revised 22 October 2015, Accepted 22 October 2015, Available online 30 October 2015, Version of Record 5 May 2016.
论文官网地址：https://doi.org/10.1016/j.elerap.2015.10.003
