Exploiting Machine Learning for Comparative Sentences Extraction
Exploiting Machine Learning for Comparative Sentences Extraction
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DOI：
10.14257/ijhit.2015.8.3.31
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发表时间：
2015-03
期刊：
影响因子：
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通讯作者：
Wei Wang;Tie-Jun Zhao;Guodong Xin;Y. Xu
中科院分区：
文献类型：
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作者：
Wei Wang;Tie-Jun Zhao;Guodong Xin;Y. Xu
本文研究的是从用户评论中抽取中文比较句的问题，这是一个句子层次上的文本分类问题。针对评论数据的类偏问题，建立了一个支持向量机（SVM）模型，在平衡数据集上对比较句和非比较句进行分类。各种语言学和统计学特征被引入来表征句子。对用户生成的产品评论进行了实验。因此，我们的实验显示出显着的性能，总体F得分为85.87%。
This paper studies the problem of extracting Chinese comparative sentences from user reviews, which is a problem of text classification in the level of sentence. This paper first deals with the class skewed problem of review data, and then builds a SVM (support vector machine) model to classify comparative and non-comparative sentences into different groups on a balanced dataset. Various linguistic and statistical features are introduced to characterize a sentence. Experiments were conducted on user-generated product reviews. As a result, our experiments show significant performance, an overall Fscore of 85.87%.