Estimating the Best Time to View Cherry Blossoms Using Time-Series Forecasting Method

Estimating the Best Time to View Cherry Blossoms Using Time-Series Forecasting Method
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DOI:
10.3390/make4020018
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发表时间:
2022-04
期刊:
Mach. Learn. Knowl. Extr.
影响因子:
--
通讯作者:
Tomonari Horikawa;Munenori Takahashi;Masaki Endo;Shigeyoshi Ohno;Masaharu Hirota;H. Ishikawa
Tomonari Horikawa;Munenori Takahashi;Masaki Endo;Shigeyoshi Ohno;Masaharu Hirota;H. Ishikawa
中科院分区:
其他
文献类型:
--
作者:
Tomonari Horikawa;Munenori Takahashi;Masaki Endo;Shigeyoshi Ohno;Masaharu Hirota;H. Ishikawa

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近年来,利用互联网收集旅游信息已经变得司空见惯。游客越来越多地使用互联网资源来获取旅游信息。社交网络服务(SNS)用户共享各种旅游信息。推特是一种社交网络,已经被用于许多研究。我们正在进行一项研究,支持一种使用Twitter帮助游客获取信息的方法:估计观赏樱花的最佳时间。早期的研究已经提出了一种低成本的移动平均方法,使用与位置信息相关的地理标记推文。带有地理标记的推文有助于作为社交传感器进行实时估计,并有助于获取当地旅游信息,因为这些信息可以反映真实世界的情况。早期的研究使用了加权移动平均数,表明一个人可以估计出每个县观赏樱花的最佳时间。本研究提出了一种使用SNS数据和机器学习的时间序列预测方法,作为一种新的方法来估计某一时段的最佳观看时间。将时间序列预测法和低成本移动平均法结合起来,可以估计出观赏樱花的最佳时间。这份报告描述了通过对每个州和直辖市观赏美丽樱花的最佳时间进行估计的实验结果,证实了所提出的方法的有效性。
In recent years, tourist information collection using the internet has become common. Tourists are increasingly using internet resources to obtain tourist information. Social network service (SNS) users share tourist information of various kinds. Twitter, one SNS, has been used for many studies. We are pursuing research supporting a method using Twitter to help tourists obtain information: estimates of the best time to view cherry blossoms. Earlier studies have proposed a low-cost moving average method using geotagged tweets related to location information. Geotagged tweets are helpful as social sensors for real-time estimation and for the acquisition of local tourist information because the information can reflect real-world situations. Earlier studies have used weighted moving averages, indicating that a person can estimate the best time to view cherry blossoms in each prefecture. This study proposes a time-series prediction method using SNS data and machine learning as a new method for estimating the best times for viewing for a certain period. Combining the time-series forecasting method and the low-cost moving average method yields an estimate of the best time to view cherry blossoms. This report describes results confirming the usefulness of the proposed method by experimentation with estimation of the best time to view beautiful cherry blossoms in each prefecture and municipality.