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Representing positional uncertainty of individual and aggregated trajectories of moving objects

Published: 05 November 2013 Publication History

Abstract

Trajectories are used to represent objects' movement and spatio-temporal aggregation of trajectories is commonly used in knowledge discovery. Based on a general workflow to extract knowledge, we identify relevant factors that propagate uncertainty in moving object datasets when using aggregation. We use a probabilistic approach and propose a theoretical model to represent positional uncertainty of trajectories and their aggregation, and implement a prototype system to compute positional uncertainty in pedestrians' movement data.

References

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COST. Memorandum of understanding for the implementation of a european concerted research action designated as COST action IC0903: Knowledge discovery from moving objects MOVE. Memorandum, European Cooperation in the field of Scientific and Technical Reseach, Brussels, Belgium, 2009.
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U. Demšar and K. Virrantaus. Space-time density of trajectories: exploring spatio-temporal patterns in movement data. International Journal of Geographical Information Science, 24(10):pp 1527--1542, 2010.
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F. Giannotti, M. Nanni, D. Pedreschi, F. Pinelli, C. Renso, S. Rinzivillo, and R. Trasarti. Unveiling the complexity of human mobility by querying and mining massive trajectory data. The VLDB Journal, 20(5):pp 695--719, 2011.
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D. Pfoser and C. Jessen. Capturing the uncertainty of moving-object representations, volume 1651, pages 111--131. Springer, Berlin, 1999.
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W. Shi and W. Liu. A stochastic process-based model for the positional error of line segments in gis. International Journal of Geographical Information Science, 14(1):51--66, 2000.
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G. Trajcevski, R. Tamassia, I. F. Cruz, P. Scheuermann, D. Hartglass, and C. Zamierowski. Ranking continuous nearest neighbors for uncertain trajectories. VLDB Journal, 20(5):767--791, 2011.
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Published In

cover image ACM Conferences
SIGSPATIAL'13: Proceedings of the 21st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
November 2013
598 pages
ISBN:9781450325219
DOI:10.1145/2525314
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 05 November 2013

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Author Tags

  1. aggregation
  2. moving objects
  3. pedestrian movement
  4. trajectories
  5. uncertainty

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  • Research-article

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  • NICHE Project

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SIGSPATIAL'13
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Overall Acceptance Rate 220 of 1,116 submissions, 20%

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