Papers by MingXue Wang

1 papers
AX-MABSA: A Framework for Extremely Weakly Supervised Multi-label Aspect Based Sentiment Analysis (2022.emnlp-main)

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Challenge: Aspect Based Sentiment Analysis is a dominant research area with potential applications in social media analytics, business, finance, and health.
Approach: They propose a weakly supervised multi-label Aspect Category Sentiment Analysis framework which does not use any labelled data.
Outcome: The proposed framework outperforms weakly supervised baselines on four benchmark datasets and is able to generate multiple aspect category-sentiment pairs per review sentence.

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