Unsupervised Japanese-Chinese Opinion Word Translation using Dependency Distance and Feature-Opinion Association Weight
نویسندگان
چکیده
Online shoppers depend on customer reviews when evaluating products or services. However, in the international online marketplace, reviews in a user’s language may not be available. Translation of online customer reviews is therefore an important service. A crucial aspect of this task is translating opinion words, key words that capture the reviewers’ sentiments. This is challenging because opinion words often have multiple translations. We propose an unsupervised opinion word translation disambiguation scoring method using dependency distance and feature-opinion association as weighting factors. The scores of an opinion word’s translation and its surrounding words’ translations are estimated using Google snippets. We focus on Japanese-Chinese translation of hotel reviews from Rakutan Travel, using the 10 most common polysemous Japanese opinion words to evaluate system performance. Results show our weighting factors significantly improve translation accuracy compared to Google and Excite.
منابع مشابه
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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-m...
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تاریخ انتشار 2012