Papers with aspect-level classifier

1 papers
Diversified Multiple Instance Learning for Document-Level Multi-Aspect Sentiment Classification (2020.emnlp-main)

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Challenge: Experimental results show that D-MILN outperforms recent weakly-supervised baselines . document-level multi-aspect sentiment classification requires a lot of manual aspect-level annotations - which is time-consuming and laborious .
Approach: They propose a novel Diversified Multiple Instance Learning Network to achieve DMSC with only document-level weak supervision.
Outcome: The proposed method outperforms weakly-supervised baselines on TripAdvisor and BeerAdvocate datasets.

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