A context-enhanced sentence representation learning method for close domains with topic modeling

Information Sciences(2022)

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摘要
•Context-enhanced mechanism fosters sentence embeddings learning in closed domains.•Bi-Directional contexts helps to learn high-quality sentence embeddings.•Model in closed domains is readily trained from scratch.•It is highly interpretable for sentence representation learning with topic modeling.
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关键词
Sentence representations learning,Closed domains,Bayesian sentence embedding,Bi-directional context-enhanced,Semantic interpretability,Topic modeling
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