Papers with affection-driven approach

1 papers
Affection Driven Neural Networks for Sentiment Analysis (2020.lrec-1)

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Challenge: Existing deep neural network models lack mechanisms to highlight important sentiment terms.
Approach: They propose a method to incorporate affective knowledge into deep neural network models by mapping affective influence vectors to an affective impact value and integrating them into long-term memory models to highlight affective terms.
Outcome: The proposed approach improves on three large datasets by 1.0% to 1.5% on the benchmark datasets.

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