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Generating spatiotemporal datasets on the WWW

Authors:

Yannis Theodoridis,

Mario A. NascimentoAuthors Info & Claims

ACM SIGMOD Record, Volume 29, Issue 3

Pages 39 - 43

https://doi.org/10.1145/362084.362104

Published: 01 September 2000 Publication History

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Abstract

Efficient storage, indexing and retrieval of time-evolving spatial data are some of the tasks that a Spatiotemporal Database Management System (STDBMS) must support. Aiming at designers of indexing methods and access structures, in this article we review the GSTD algorithm for generating spatiotemporal datasets according to several user-defined parameters, and introduce a WWW-based environment for generating and visualizing such datasets. The GSTD interface is available at two main sites: http://www.cti.gr/RD3/GSTD/ and http://www.cs.ualberta.ca/~mn/GSTD/.

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Wei TLin YGuo SLin YHuang YXiang CBai YWan H(2024)Diff-RNTraj: A Structure-Aware Diffusion Model for Road Network-Constrained Trajectory GenerationIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2024.346005136:12(7940-7953)Online publication date: 1-Dec-2024
https://dl.acm.org/doi/10.1109/TKDE.2024.3460051
Zhang LZhao LPfoser DRenz MSarwat M(2022)Factorized deep generative models for end-to-end trajectory generation with spatiotemporal validity constraintsProceedings of the 30th International Conference on Advances in Geographic Information Systems10.1145/3557915.3560994(1-12)Online publication date: 1-Nov-2022
https://dl.acm.org/doi/10.1145/3557915.3560994
Lee SHong BKim W(2022)A generation of synthesized trajectories of free moving objects for testing a set of continuous spatio‐temporal queriesConcurrency and Computation: Practice and Experience10.1002/cpe.714734:20Online publication date: 22-Jun-2022
https://doi.org/10.1002/cpe.7147
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Generating spatiotemporal datasets on the WWW

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ACM SIGMOD Record Volume 29, Issue 3

Sept. 2000

86 pages

ISSN:0163-5808

DOI:10.1145/362084

Editor:
Michael Franklin
Univ. of California, Berkeley

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Association for Computing Machinery

New York, NY, United States

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Published: 01 September 2000

Published in SIGMOD Volume 29, Issue 3

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Wei TLin YGuo SLin YHuang YXiang CBai YWan H(2024)Diff-RNTraj: A Structure-Aware Diffusion Model for Road Network-Constrained Trajectory GenerationIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2024.346005136:12(7940-7953)Online publication date: 1-Dec-2024
https://dl.acm.org/doi/10.1109/TKDE.2024.3460051
Zhang LZhao LPfoser DRenz MSarwat M(2022)Factorized deep generative models for end-to-end trajectory generation with spatiotemporal validity constraintsProceedings of the 30th International Conference on Advances in Geographic Information Systems10.1145/3557915.3560994(1-12)Online publication date: 1-Nov-2022
https://dl.acm.org/doi/10.1145/3557915.3560994
Lee SHong BKim W(2022)A generation of synthesized trajectories of free moving objects for testing a set of continuous spatio‐temporal queriesConcurrency and Computation: Practice and Experience10.1002/cpe.714734:20Online publication date: 22-Jun-2022
https://doi.org/10.1002/cpe.7147
Lee SHong BKim W(2021)Verification of spatiotemporal continuous complex event processing rules by a synthesized data setTENCON 2021 - 2021 IEEE Region 10 Conference (TENCON)10.1109/TENCON54134.2021.9707251(614-619)Online publication date: 7-Dec-2021
https://doi.org/10.1109/TENCON54134.2021.9707251
Lee SHong BKim W(2021)A trajectory synthesis of free moving objects for continuous queries2021 International Conference on INnovations in Intelligent SysTems and Applications (INISTA)10.1109/INISTA52262.2021.9548615(1-6)Online publication date: 25-Aug-2021
https://doi.org/10.1109/INISTA52262.2021.9548615
Melo APaulheim H(2017)Synthesizing Knowledge Graphs for Link and Type Prediction BenchmarkingThe Semantic Web10.1007/978-3-319-58068-5_9(136-151)Online publication date: 28-May-2017
https://dl.acm.org/doi/10.1007/978-3-319-58068-5_9
Lee JHong JHong BAhn J(2016)A generator of test data set for tactical moving objects based on velocity2016 IEEE International Conference on Big Data (Big Data)10.1109/BigData.2016.7841093(4011-4013)Online publication date: Dec-2016
https://doi.org/10.1109/BigData.2016.7841093
Wang LHu KKu TYan X(2013)Mining frequent trajectory pattern based on vague space partitionKnowledge-Based Systems10.5555/2770959.277106150:C(100-111)Online publication date: 1-Sep-2013
https://dl.acm.org/doi/10.5555/2770959.2771061
Wang LHu KKu TYan X(2013)Mining frequent trajectory pattern based on vague space partitionKnowledge-Based Systems10.1016/j.knosys.2013.06.00250(100-111)Online publication date: Sep-2013
https://doi.org/10.1016/j.knosys.2013.06.002
Xu JGuting R(2012)MWGenProceedings of the 2012 IEEE 13th International Conference on Mobile Data Management (mdm 2012)10.1109/MDM.2012.39(258-267)Online publication date: 23-Jul-2012
https://dl.acm.org/doi/10.1109/MDM.2012.39
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