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Graph Adaptive Semantic Transfer for Cross-domain Sentiment Classification. (arXiv:2205.08772v1 [cs.CL])
May 19, 2022, 1:11 a.m. | Kai Zhang, Qi Liu, Zhenya Huang, Mingyue Cheng, Kun Zhang, Mengdi Zhang, Wei Wu, Enhong Chen
cs.CL updates on arXiv.org arxiv.org
Cross-domain sentiment classification (CDSC) aims to use the transferable
semantics learned from the source domain to predict the sentiment of reviews in
the unlabeled target domain. Existing studies in this task attach more
attention to the sequence modeling of sentences while largely ignoring the rich
domain-invariant semantics embedded in graph structures (i.e., the
part-of-speech tags and dependency relations). As an important aspect of
exploring characteristics of language comprehension, adaptive graph
representations have played an essential role in recent years. To …
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