基于依赖句法分析的日本电子商务网站经验提取

Kazuki Hagiwara, Kazuki Ono, K. Hatano
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引用次数: 1

摘要

近年来,电子商务的扩张导致网站上的客户评论数量迅速增加。一般来说,评论是消费者在购买或使用产品后写的。然而,评论可能不仅仅是由有产品经验的用户撰写的,这使得在购买商品时很难确定哪些评论是有用的参考。特别是在电子商务网站上,实际使用过或购买过商品的消费者所写的评论对消费者和商店都很有用,因此需要一种提取这种体验信息的方法。在本文中,我们提出了一种使用日文依赖解析提取包含有用信息的评论的方法。我们的方法比以前的方法提取的信息要少得多,但需要更少的处理才能达到与传统方法几乎相同的精度。
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Extracting Experiences Using Dependency Parsing on Japanese e-Commerce Websites
In recent years, the expansion of e-commerce has led to a rapid increase in the number of customer reviews on websites. In general, the reviews are written by consumers after they have purchased or used the products. However, reviews may not only be written by users who have experience of the products, making it difficult to determine which reviews are useful references when purchasing items. On e-commerce websites, in particular, reviews written by consumers who have actually used or purchased the items are useful to both consumers and shops, so a method of extracting such experiential information is needed. In this paper, we propose a method for extracting reviews that contain useful information using Japanese dependency parsing. Our method extracts rather less information than previous methods, but requires less processing to achieve almost the same accuracy as conventional approaches.
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