文本褒贬倾向判别研究

Research on text commendatory-derogatory orientation discrimination

在文本的向量空间表示模型下,针对文本褒贬倾向判别问题,提出了一种基于潜在语义分析的特征权重计算方法。除词频信息外,该方法考虑了潜在语义分析所提供的同义词、近义词信息对特征权重的影响。采用基于Fisher判别准则的特征选择方法,以支持向量机作为分类器,在2739篇语料(2008年中文倾向性分析评测)上进行了实验。实验结果表明,提出的特征权重计算方法对文本褒贬倾向判别是有效的。

On the basis of vector space model of text expression,a feature weight computing method for text commendatory-derogatory orientation discrimination is proposed based on Probabilistic Latent Semantic Analysis（PLSA）.In addition to the word frequency of a feature,the information of its thesaurus and homoionym latently obtained by PLSA is taken in consider- ation to weight computing.Using the feature selection method based on Fisher criterion,and constructing a classifier with Sup- port Vector Machine（SVM）,an experiment is conducted under a Chinese review text corpus with size of 2 739 documents （COAE2008）.The experimental results indicate that the presented weight computing method based on PLSA is effective.