Time-focused clustering of trajectories of moving objects

By Mirco Nanni, Dino Pedreschi. Journal of Intelligence and Information Systems, 2006

465 citations recorded by the source corpus.

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A clustering-based approach for discovering interesting places in trajectories (2008, background): “Several works for trajectory clustering have been developed to find similar subtrajectories or dense regions as [9], [11], [13].”
The [Limited] Impact of Weather on Tourist Behavior in an Urban Destination (2015, background): “Research in this field grows out of the increasing availability of spatiotemporal data and the lack of techniques to analyze it (D’Urso and Massari 2013; Nanni and Pedreschi 2006; Spaccapietra et al. 2008).”
A review of moving object trajectory clustering algorithms (2016, background): “Nanni and Pedreschi (2006) proposes T-OPTICS as an adaption of OPTICS to cluster trajectory data with another notion of distance between trajectories.”
Unveiling the complexity of human mobility by querying and mining massive trajectory data (2011, methodology): “Output: Reachability plot, a high-level description of the clustering structure of the input trajectories, obtained using the density-based trajectory clustering method of [29].”
Clustering Algorithms Research (2008, unknown): “2006 年,Micro 等人([35])面向移动对象轨迹数据处理领域,基于简单的轨迹间距离概念,提出了一种基于密度”