Papers with constrained attention networks

1 papers
CAN: Constrained Attention Networks for Multi-Aspect Sentiment Analysis (D19-1)

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Challenge: Existing methods for aspect-specific sentiment classification are noisy and downgraded performance.
Approach: They propose a constrained attention network to regularize attention for multi-aspect sentiment analysis by orthogonal regularization on multiple aspects and sparse regularization for each single aspect.
Outcome: The proposed approach outperforms state-of-the-art methods on two public datasets and extends to multi-task settings.

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