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Japanese Sentiment Classification using a Tree-Structured Long Short-Term Memory with Attention

Abstract · Apr 4, 2017 09:08 ·

cs-cl

Arxiv Abstract

  • Ryosuke Miyazaki
  • Mamoru Komachi

Previous approaches to training syntax-based sentiment classification models required phrase-level annotated corpora, which are not readily available in many languages other than English. Thus, we propose the use of tree-structured Long Short-Term Memory with an attention mechanism that pays attention to each subtree of the parse tree. Experimental results indicate that our model achieves the state-of-the-art performance in a Japanese sentiment classification task.

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