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A study on topic models using LDA and Word2Vec in travel route recommendation: focus on convergence travel and tours reviews
Personal and Ubiquitous Computing Pub Date : 2020-10-29 , DOI: 10.1007/s00779-020-01476-2
Seong-Taek Park , Chang Liu

At present, we live in prosperity contrary to the past times. As income increases, people enjoy wealth, but more people tend to pursue their own inner happiness: travel. People go to other places or visit foreign countries for business or journey. This study aims to identify the best tour route for foreign tourists in South Korea. Based on the review analysis results, this paper also aims to put forward techniques and methodologies required in practical affairs when developing a travel site or a travel application. On this note, it collected tourists’ reviews at the Tripadvisor official website and conducted text mining technique as well as network analysis using R and Tagxedo, which is a big data analytic tool. The analysis results displayed that there were differences in travel preference, and especially, individual travelers had difficulty traveling by public transportation and selecting travel destinations. Therefore, customized travel routes were suggested for convenient use among travelers.



中文翻译:

关于在旅行路线推荐中使用LDA和Word2Vec的主题模型的研究:关注融合旅行和旅行评论

当前,我们生活在与过去相反的繁荣中。随着收入的增加,人们享受财富,但是越来越多的人倾向于追求自己内心的幸福:旅行。人们去其他地方或访问国外进行商务或旅行。这项研究旨在确定韩国外国游客的最佳旅游路线。基于审查分析结果,本文还旨在提出在开发旅行站点或旅行应用程序时在实际事务中所需的技术和方法。对此,它在Tripadvisor官方网站上收集了游客的评论,并使用R和Tagxedo(这是一个大数据分析工具)进行了文本挖掘技术以及网络分析。分析结果表明,出行偏好存在差异,特别是,个别旅行者在乘坐公共交通工具旅行和选择旅行目的地时遇到困难。因此,建议定制旅行路线以方便旅行者使用。

更新日期:2020-10-30
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