文章基本信息

标题：Diverse Opinions Extraction from Web Reviews Based on Word Frequency Distribution for Each Evaluation Value
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作者：Ayaka Kodaira ; Ryosuke Yamanishi ; Yoko Nishihara 等
期刊名称：Lecture Notes in Engineering and Computer Science
印刷版ISSN：2078-0958
电子版ISSN：2078-0966
出版年度：2019
卷号：2239
页码：231-235
出版社：Newswood and International Association of Engineers
摘要：This paper proposes a method for extracting various opinions about evaluation points from web reviews. In the proposed method, the evaluation points which frequency is different for each evaluation value such as stars. Opinions in reviews with extremely high or low evaluation values are effective to evaluate the review targets in most cases. However, the reviewers themselves are diverse. The evaluation points that many reviewers highly evaluated sometimes can be the cause of the low evaluation in a specific context for the same target. It is thus reasonable to say that comparing those conflicted opinions should help us to understand the features of the services and products. To provide such findings to the readers, focusing on not only the evaluation points which has high frequency but also various opinions in different context should be required. In this paper, we conducted the extraction experiment and had the discussion about the extracted opinions.
关键词：review analysis; diverse opinions; web intelligence