Grouping time-varying data for interactive exploration

A.I. van Goethem, M.J. van Kreveld, M. Löffler, B. Speckmann, F. Staals

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

5 Citations (Scopus)
20 Downloads (Pure)

Abstract

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.
Original languageEnglish
Title of host publicationProc. of the 32nd annual Symposium on Computational Geometry (SoCG)
PublisherDagstuhl Publishing
Pages1-16
DOIs
Publication statusPublished - 2016
Event32nd International Symposium on Computational Geometry (SoCG 2016) - Boston, United States
Duration: 14 Jun 201618 Jun 2016

Conference

Conference32nd International Symposium on Computational Geometry (SoCG 2016)
CountryUnited States
CityBoston
Period14/06/1618/06/16

Fingerprint

Dive into the research topics of 'Grouping time-varying data for interactive exploration'. Together they form a unique fingerprint.

Cite this