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Spatial structures of tourism destinations: A trajectory data mining approach leveraging mobile big data
Annals of Tourism Research ( IF 10.4 ) Pub Date : 2020-09-01 , DOI: 10.1016/j.annals.2020.102973
Sangwon Park , Yang Xu , Liu Jiang , Zhelin Chen , Shuyi Huang

Abstract The advancement of mobile technology provides an opportunity to obtain the real-time information of travelers, such as their spatial and temporal behaviors, during their visits to a destination. This study analyzes a large scale mobile phone dataset that captures the cellphone trace of international travelers who visited South Korea. We apply a trajectory data mining approach to understand the spatial structures of tourist activities within three different destinations. Through spatial clustering analysis and sequential pattern mining, the study reveals multiple “hot spots” (or popular areas) in travel destinations and spatial interactions across these places. As a result, this paper provides important tourism implications integrating spatial models with destination planning, which is the foundation of tourism design.

中文翻译:

旅游目的地空间结构:利用移动大数据的轨迹数据挖掘方法

摘要 移动技术的进步为获取旅行者在访问目的地期间的时空行为等实时信息提供了机会。本研究分析了一个大规模的手机数据集,该数据集捕获了访问韩国的国际旅行者的手机轨迹。我们应用轨迹数据挖掘方法来了解三个不同目的地内旅游活动的空间结构。通过空间聚类分析和序列模式挖掘,该研究揭示了旅游目的地的多个“热点”(或热门区域)以及这些地方的空间交互。因此,本文提供了将空间模型与目的地规划相结合的重要旅游意义,这是旅游设计的基础。
更新日期:2020-09-01
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