计算机科学 ›› 2020, Vol. 47 ›› Issue (11): 275-279.doi: 10.11896/jsjkx.191000174
马晓慧1, 贾君枝2, 周湘贞3, 闫俊伢1
MA Xiao-hui1, JIA Jun-zhi2, ZHOU Xiang-zhen3, YAN Jun-ya1
摘要： 情感词典有助于情感分析,可以通过词语匹配来进行情感分类。但是,情感词典在词汇覆盖和领域适应方面存在一定的局限性。为此,文中提出了一种基于语义相似性度量和嵌入表示的情感分类方法,该方法计算了待分类文本与情感词典之间的语义相似度,将语义距离和基于嵌入的特征结合起来进行情感分类,有助于解决语义特征利用不足的问题。文中分别采用词向量、情感词典匹配和所提方法提取的特征向量来对情感分类性能进行了评估。实验结果表明,所提方法整体上优于对比方法。在3种电商评论测试语料中,所提方法的F1平均值达到了83.46%,相比对比方法提升了8.26%。其中,利用词嵌入与ECSD(E-Commerce Sentiment Dictionary)相结合提取的语义分类效果最佳,性能提升达到了9%,表明通过结合语义相似度可以丰富提取的情感语义特征,能够有效提升情感分类的性能。
中图分类号:
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