A Proposal of a Method to Automatically Estimate Evaluations of Various Topics of Travelers' Reviews

2016 5th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI) Pub Date : 2016-07-10 DOI:10.1109/IIAI-AAI.2016.146

Kosuke Kawabata, M. Okada, N. Mori, Kiyota Hashimoto

引用次数: 2

Abstract

Generally, evaluations in customer reviews are shown with text and score. In addition, there are 2 kinds of scored evaluations, which are a comprehensive evaluation and topic evaluations. However, topic evaluations are not often given by reviewers. Therefore, it is required to estimate the evaluations. In this paper, we researched a performance of estimation by SVM. Furthermore, we compared results of estimation by SVM and scanning with dependency relation tree. The result shew that precision of estimation by each method is low. On the other hand, the result shew that precision in positive score is over about 70% in each topic.

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一种自动估计不同主题旅客评论评价的方法

通常，客户评论中的评价以文本和分数显示。此外，还有两种得分评价，即综合评价和主题评价。然而，主题评估通常不是由审稿人给出的。因此，需要对评价进行估计。本文研究了支持向量机的估计性能。此外，我们比较了基于依赖关系树的支持向量机估计和扫描估计的结果。结果表明，每种方法的估计精度都较低。另一方面，结果表明，每个主题的正确率都在70%左右。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

2016 5th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI)

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