Discovering Correspondence of Sentiment Words and Aspects
CICLing, pp. 233-245, 2016.
Extracting aspects and sentiments is a key problem in sentiment analysis. Existing models rely on joint modeling with supervised aspect and sentiment switching. This paper explores unsupervised models by exploiting a novel angle – correspondence of sentiments with aspects via topic modeling under two views. The idea is to split documents ...More
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