Efficient Mining of Volunteered Trajectory Datasets

dc.contributor.authorForsch, Axel
dc.contributor.authorFunke, Stefan
dc.contributor.authorHaunert, Jan-Henrik
dc.contributor.authorStorandt, Sabine
dc.date.accessioned2024-01-05T08:26:53Z
dc.date.available2024-01-05T08:26:53Z
dc.date.issued2024
dc.description.abstractWith the ubiquity of mobile devices that are capable of tracking positions (be it via GPS or Wi-Fi/mobile network localization), there is a continuous stream of location data being generated every second. These location measurements are typically not considered individually but rather as sequences, each of which reflects the movement of one person or vehicle, which we call trajectory. This chapter presents new algorithmic approaches to process and visualize trajectories both in the network-constrained and the unconstrained case.
dc.description.versionpublisheddeu
dc.identifier.doi10.1007/978-3-031-35374-1_3
dc.identifier.ppn1879091844
dc.identifier.urihttps://kops.uni-konstanz.de/handle/123456789/68939
dc.language.isoeng
dc.rightsAttribution 4.0 International
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subject.ddc004
dc.titleEfficient Mining of Volunteered Trajectory Datasetseng
dc.typeINCOLLECTION
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  year={2024},
  doi={10.1007/978-3-031-35374-1_3},
  title={Efficient Mining of Volunteered Trajectory Datasets},
  isbn={978-3-031-35373-4},
  publisher={Springer Nature},
  address={Cham},
  booktitle={Volunteered Geographic Information : Interpretation, Visualization and Social Context},
  pages={43--77},
  editor={Burghardt, Dirk and Demidova, Elena and Keim, Daniel A.},
  author={Forsch, Axel and Funke, Stefan and Haunert, Jan-Henrik and Storandt, Sabine}
}
kops.citation.iso690FORSCH, Axel, Stefan FUNKE, Jan-Henrik HAUNERT, Sabine STORANDT, 2024. Efficient Mining of Volunteered Trajectory Datasets. In: BURGHARDT, Dirk, ed., Elena DEMIDOVA, ed., Daniel A. KEIM, ed.. Volunteered Geographic Information : Interpretation, Visualization and Social Context. Cham: Springer Nature, 2024, pp. 43-77. ISBN 978-3-031-35373-4. Available under: doi: 10.1007/978-3-031-35374-1_3deu
kops.citation.iso690FORSCH, Axel, Stefan FUNKE, Jan-Henrik HAUNERT, Sabine STORANDT, 2024. Efficient Mining of Volunteered Trajectory Datasets. In: BURGHARDT, Dirk, ed., Elena DEMIDOVA, ed., Daniel A. KEIM, ed.. Volunteered Geographic Information : Interpretation, Visualization and Social Context. Cham: Springer Nature, 2024, pp. 43-77. ISBN 978-3-031-35373-4. Available under: doi: 10.1007/978-3-031-35374-1_3eng
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kops.sourcefieldBURGHARDT, Dirk, ed., Elena DEMIDOVA, ed., Daniel A. KEIM, ed.. <i>Volunteered Geographic Information : Interpretation, Visualization and Social Context</i>. Cham: Springer Nature, 2024, pp. 43-77. ISBN 978-3-031-35373-4. Available under: doi: 10.1007/978-3-031-35374-1_3deu
kops.sourcefield.plainBURGHARDT, Dirk, ed., Elena DEMIDOVA, ed., Daniel A. KEIM, ed.. Volunteered Geographic Information : Interpretation, Visualization and Social Context. Cham: Springer Nature, 2024, pp. 43-77. ISBN 978-3-031-35373-4. Available under: doi: 10.1007/978-3-031-35374-1_3deu
kops.sourcefield.plainBURGHARDT, Dirk, ed., Elena DEMIDOVA, ed., Daniel A. KEIM, ed.. Volunteered Geographic Information : Interpretation, Visualization and Social Context. Cham: Springer Nature, 2024, pp. 43-77. ISBN 978-3-031-35373-4. Available under: doi: 10.1007/978-3-031-35374-1_3eng
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source.contributor.editorBurghardt, Dirk
source.contributor.editorDemidova, Elena
source.contributor.editorKeim, Daniel A.
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source.publisherSpringer Nature
source.publisher.locationCham
source.titleVolunteered Geographic Information : Interpretation, Visualization and Social Context

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