Papers by Chenggong Gong

2 papers
Cross-Domain Review Generation for Aspect-Based Sentiment Analysis (2021.findings-acl)

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Challenge: Existing domain adaptation methods for Aspect-Based Sentiment Analysis lack finegrained labeled data.
Approach: They propose a new domain adaptation paradigm called cross-domain review generation which aims to generate target-domain reviews with fine-grained annotation based on the labeled source domain.
Outcome: The proposed approach is superior to state-of-the-art domain adaptation methods.
Unified Feature and Instance Based Domain Adaptation for Aspect-Based Sentiment Analysis (2020.emnlp-main)

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Challenge: Existing approaches to aspect-based sentiment analysis rely on labeled data, but they lack the fine-grained labeles needed for the ABSA task.
Approach: They propose a framework to perform feature adaptation and instance adaptation for the ABSA task . they learn domain-invariant feature representations by using part-of-speech features .
Outcome: The proposed method improves on the state-of-the-art in two aspects of the ABSA task.

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