Cross-Domain Text Classification
6 papers with code • 0 benchmarks • 0 datasets
Learning an accurate model for the new unlabeled target domain given labeled data from multiple source domains where all domains have (possibly) different label sets. (Source: https://www.aclweb.org/anthology/P16-1155.pdf)
Benchmarks
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Most implemented papers
Multinomial Adversarial Networks for Multi-Domain Text Classification
Many text classification tasks are known to be highly domain-dependent.
Hierarchical Attention Transfer Network for Cross-Domain Sentiment Classification
hsqmlzno1/HATN
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Thirty-Second AAAI Conference on Artificial Intelligence 2018
Existing cross-domain sentiment classification meth- ods cannot automatically capture non-pivots, i. e., the domain- specific sentiment words, and pivots, i. e., the domain-shared sentiment words, simultaneously.
Cross-Domain Labeled LDA for Cross-Domain Text Classification
To this end, we embed the group alignment and a partial supervision into a cross-domain topic model, and propose a Cross-Domain Labeled LDA (CDL-LDA).
Multiple-Source Domain Adaptation via Coordinated Domain Encoders and Paired Classifiers
p-karisani/CEPC
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We present a novel multiple-source unsupervised model for text classification under domain shift.
TACIT: A Target-Agnostic Feature Disentanglement Framework for Cross-Domain Text Classification
However, these methods rely on unlabeled samples provided by the target domains, which renders the model ineffective when the target domain is agnostic.
