Spatiotemporal trajectory clustering: A clustering algorithm for spatiotemporal data
作者：
Highlights：
• Development of a novel spatiotemporal clustering algorithm for trajectory clustering.
• Implementation of visualization tool to validate the clusters.
• Experimentation on two different real datasets.
• The developed algorithm has ability to effectively discover quality clusters.
• This approach has many real-world applications.
摘要
•Development of a novel spatiotemporal clustering algorithm for trajectory clustering.•Implementation of visualization tool to validate the clusters.•Experimentation on two different real datasets.•The developed algorithm has ability to effectively discover quality clusters.•This approach has many real-world applications.
论文关键词：Density-based clustering,Trajectory clustering,Spatiotemporal data,Co-location events
论文评审过程：Received 8 August 2019, Revised 17 March 2021, Accepted 14 April 2021, Available online 20 April 2021, Version of Record 4 May 2021.
论文官网地址：https://doi.org/10.1016/j.eswa.2021.115048
