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文章基本信息

  • 标题:Aspect Identification of Sentiment Sentences Using A Clustering Algorithm
  • 本地全文:下载
  • 作者:Masashi Hadano ; Masashi Hadano ; Kazutaka Shimada
  • 期刊名称:Procedia - Social and Behavioral Sciences
  • 印刷版ISSN:1877-0428
  • 出版年度:2011
  • 卷号:27
  • 页码:22-31
  • DOI:10.1016/j.sbspro.2011.10.579
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractReviews contain aspect information of a product, such as “image quality” and “usability” of a camera. In this paper, we propose an aspect identification method for sentiment sentences in review documents. Machine learning methods usually require a large amount of training data for generating a classifier with high accuracy. However, preparing training data by hand is costly. To solve this problem, we apply a clustering approach to the aspect identification method. Our system acquires new training data from non-tagged data by using the clustering approach. As compared with a baseline method, which does not use the acquisition approach, our method obtained high accuracy.
  • 关键词:Sentiment analysis;Aspect identification;Clustering
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