基于概率潜在语义分析的词汇情感倾向判别

该文利用概率潜在语义分析,给出了两种用于判别词汇情感倾向的方法。一是使用概率潜在语义分析获得目标词和基准词之间的相似度矩阵,再利用投票法决定其情感倾向;二是利用概率潜在语义分析获取目标词的语义聚类,然后借鉴基于同义词的词汇情感倾向判别方法对目标词的情感倾向做出判别。两种方法的优点是均可在没有外部资源的条件下,实现词汇情感倾向的判别。

Word Sentiment Orientation Discrimination Based on PLSA

This paper proposes two kinds of methods to determine the sentiment orientation of a word based on Probabilistic Latent Semantic Analysis(PLSA). In the first method, the similarity matrix between target words and paradigm words is obtained by PLSA, and the polarity of each target word is then determined by voting. In the second method, we obtain the semantic cluster of target words by PLSA, and the polarity of a target word is then determined by a synonym-based method. The advantage to both methods lies in that they can work well without any external knowledge resources.
Key wordsprobabilistic latent semantic analysis; sparse data; semantic clustering; sentiment orientation