Papers with structural correspondence learning

1 papers
Projecting Embeddings for Domain Adaption: Joint Modeling of Sentiment Analysis in Diverse Domains (C18-1)

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Challenge: Existing domain adaptation methods for sentiment analysis are sensitive to domain differences, resulting in classifiers that perform poorly on new domains.
Approach: They propose a domain adaptation problem as an embedding projection task using two mono-domain embeddable spaces and a bi-domain space to project across domains and predict sentiment.
Outcome: The proposed model performs better on domains similar to state-of-the-art methods while requiring longer training times.

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