Papers with LBSA

1 papers
A Lexicon-Based Supervised Attention Model for Neural Sentiment Analysis (C18-1)

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Challenge: Existing attention models do not take full advantage of sentiment lexicons, which provide rich sentiment information and play a critical role in sentiment analysis.
Approach: They propose a lexicon-based supervised attention model which allows a neural network to focus on the sentiment content, thus generating sentiment-informative representations.
Outcome: The proposed model outperforms existing models on three large-scale sentiment classification datasets.

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