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现在使用创新的人类流动性数据进行旅游夜晚的播放
Umberto Minora1, Stefano Maria Iacus2, Filipe Batista E Silva1
1European Commission, Joint Research Centre, Ispra, Italy.
PloS one
|October 13, 2023
概括
谷歌社区流动性报告现在可以高准确地预测旅游需求. 这种新型数据源为旅游统计提供了及时的见解,尽管存在隐私问题,但有助于管理.
科学领域:
- 旅游研究旅游研究
- 数据科学是数据科学.
- 时间空间分析.
背景情况:
- 旅游业统计数据往往落后于动态需求,特别是在危机期间.
- 及时的数据对于有效的旅游监测和管理至关重要.
- 像数字痕迹这样的替代数据源提供了潜在的解决方案.
研究的目的:
- 探索谷歌社区流动性报告的潜力,以预测旅游需求.
- 评估人类流动性数据在预测月度酒店住宿的准确性.
- 为了比较移动数据与网络搜索和手机数据的有效性,用于旅游分析.
主要方法:
- 利用机器学习模型来分析人类移动数据.
- 专注于2020年至2022年中期的11个欧洲国家.
- 将预测性能与传统和替代数据源进行比较.
主要成果:
- 人类流动数据在现在预测旅游需求 (每月度过的夜晚) 中显示出高准确度.
- 谷歌社区流动性报告显示,实时旅游统计的巨大潜力.
- 与网络搜索和手机数据相比,性能具有竞争力.
结论:
- 人类流动性数据为旅游需求预测提供了可行,准确和及时的替代方案.
- 这有助于更频繁,更灵活地制作旅游统计数据.
- 隐私和监控问题仍然是广泛采用的挑战.
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