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

Ryosuke Miyazaki; Mamoru Komachi

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arXiv · 1704.00924

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

Ryosuke Miyazaki·Mamoru Komachi

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Abstract

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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Ryosuke Miyazaki, Mamoru Komachi. 2017-04-04. Japanese Sentiment Classification using a Tree-Structured Long Short-Term Memory with Attention. https://arxiv.org/abs/1704.00924

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