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  • 标题:Opinion Mining from Web Documents: Extraction and Structurization
  • 本地全文:下载
  • 作者:Nozomi Kobayashi ; Kentaro Inui ; Yuji Matsumoto
  • 期刊名称:人工知能学会論文誌
  • 印刷版ISSN:1346-0714
  • 电子版ISSN:1346-8030
  • 出版年度:2007
  • 卷号:22
  • 期号:2
  • 页码:227-238
  • DOI:10.1527/tjsai.22.227
  • 出版社:The Japanese Society for Artificial Intelligence
  • 摘要:The task of opinion extraction and structurization is the key component of opinion mining, which allow Web users to retrieve and summarize people's opinions scattered over the Internet. Our aim is to develop a method for extracting opinions that represent evaluation of concumer products in a structured form. To achieve the goal, we need to consider some issues that are relevant to the extraction task: How the task of opinion extraction and structurization should be designed, and how to extract the opinions which we defined. We define an opinion unit consisting of a quadruple, that is, the opinion holder, the subject being evaluated, the part or the attribute in which it is evaluated, and the evaluation that expresses positive or negative assessment. In this task, we focus on two subtasks (a) extracting subject/aspect-evaluation relations, and (b) extracting subject/aspect-aspect relations, we approach each extraction task using a machine learning-based method. In this paper, we discuss how customer reviews in web documents can be best structured. We also report on the results of our experiments and discuss future directions.
  • 关键词:opinion mining ; sentiment analysis ; information extraction ; relation extraction
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