文章基本信息

标题：Grouping Time-Varying Data for Interactive Exploration
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作者：Arthur van Goethem ; Marc van Kreveld ; Maarten L{\"o}ffler 等
期刊名称：LIPIcs : Leibniz International Proceedings in Informatics
电子版ISSN：1868-8969
出版年度：2016
卷号：51
页码：61:1-61:16
DOI：10.4230/LIPIcs.SoCG.2016.61
出版社：Schloss Dagstuhl -- Leibniz-Zentrum fuer Informatik
摘要：We present algorithms and data structures that support the interactive analysis of the grouping structure of one-, two-, or higher-dimensional time-varying data while varying all defining parameters. Grouping structures characterise important patterns in the temporal evaluation of sets of time-varying data. We follow Buchin et al. [JoCG 2015] who define groups using three parameters: group-size, group-duration, and inter-entity distance. We give upper and lower bounds on the number of maximal groups over all parameter values, and show how to compute them efficiently. Furthermore, we describe data structures that can report changes in the set of maximal groups in an output-sensitive manner. Our results hold in R^d for fixed d.
关键词：Trajectory; Time series; Moving entity; Grouping; Algorithm; Data structure