Apr 17, 2021 · We propose the BertMasker network which explicitly masks domain-related words from texts, learns domain-invariant sentiment features from these domain-agnostic ...
May 7, 2022 · We propose the BERTMasker model which explicitly masks domain-related words from texts, learns domain-invariant sentiment features from these domain-agnostic ...
In this work, we focus on the task of multi-domain sentiment classification (MDSC) where we need to make full use of limited annotated data and large unlabeled ...
We describe a sentiment classification method that is applicable when we do not have any labeled data for a target domain but have some labeled data for ...
Multi-domain sentiment classification deals with the scenario where labeled data exists for multiple domains but insufficient for training effective sentiment ...
Learning to share by masking the non-shared for multi-domain sentiment classification. https://doi.org/10.1007/s13042-022-01556-0.
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Learning to Share by Masking the Non-shared for Multi-domain Sentiment Classification. ... Recent advances in deep learning based sentiment analysis. [pdf]
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Jun 7, 2023 · Learning to share by masking the non-shared for multi-domain sentiment classification. International Journal of Machine Learning and ...
Dec 29, 2022 · We propose a model for cross-domain sentiment classification, which is based on decoding-enhanced BERT with disentangled attention (DeBERTa).