文章基本信息

标题：Opinion Mining from Web Documents: Extraction and Structurization
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作者：Nozomi Kobayashi ; Kentaro Inui ; Yuji Matsumoto 等
期刊名称：Information and Media Technologies
电子版ISSN：1881-0896
出版年度：2007
卷号：2
期号：1
页码：326-337
DOI：10.11185/imt.2.326
出版社：Information and Media Technologies Editorial Board
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