Japanese opinion word translation based on unsupervised word sense disambiguation in the travel domain

This paper proposes a Japanese opinion word translation method based on unsupervised word sense disambiguation. The method comprises the corpus preparation, opinion word dictionary construction, and weighting method. Different from the machine translation, our method does not need parallel corpora, tagged corpora or parsing tree banks. Our method is low-cost but effective, and requires a well-made bilingual dictionary only. Besides, our method can extract key information from the opinions to help users understand the opinions. We construct four configurations and evaluate our method on four Japanese opinion words with high frequency. The evaluation result shows that the dependency grammar and opinion word dictionary is effective on opinion word translation. Our method can deal with the translation disambiguation problem and improve the translation precision to help user realize Japanese opinions.