Papers by Lingxian Bao

1 papers
Attention and Lexicon Regularized LSTM for Aspect-based Sentiment Analysis (P19-2)

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Challenge: End-to-end deep learning systems lack flexibility as one cannot adjust the network to fix an obvious problem.
Approach: They propose a way to leverage lexicon information to make the model more flexible . they also explore the effect of regularizing attention vectors to allow the network to have a broader "focus"
Outcome: The proposed approach leverages lexicon information to make it more flexible and robust.

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