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MOVELETS: exploring relevant subtrajectories for robust trajectory classification

Published: 09 April 2018 Publication History

Abstract

Several methods for trajectory classification build models exploring trajectory global features, such as the average and the standard deviation of speed and acceleration, but for some applications these features may not be the best to determine the class. Other works explore local features, applying trajectory partition and discretization, that lose important movement information that could discriminate the class. In this work we propose a new method, called Movelets, to discover relevant subtrajectories without the need of a predefined criteria for either trajectory partition or discretization. We extend the concept of time series shapelets for trajectories, and to the best of our knowledge, this work is the first to use shapelets in the trajectory domain. We evaluated the proposed approach with several categories of datasets, including hurricanes, vehicles, animals, and transportation means, and show with extensive experiments that our method largely outperformed state of the art works, indicating that Movelets is very promising for trajectory classification.

References

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Cited By

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  • (2024)Trajectory Mining and Routing: A Cross-Sectoral ApproachJournal of Marine Science and Engineering10.3390/jmse1201015712:1(157)Online publication date: 12-Jan-2024
  • (2024)Trajectory User Linking With Self Organizing TreesProceedings of the 1st ACM SIGSPATIAL International Workshop on Geospatial Anomaly Detection10.1145/3681765.3698450(28-31)Online publication date: 29-Oct-2024
  • (2024)Improving trajectory classification through Kramers–Moyal coefficientsAI Open10.1016/j.aiopen.2024.06.0015(87-93)Online publication date: 2024
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      cover image ACM Conferences
      SAC '18: Proceedings of the 33rd Annual ACM Symposium on Applied Computing
      April 2018
      2327 pages
      ISBN:9781450351911
      DOI:10.1145/3167132
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      Published: 09 April 2018

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      Author Tags

      1. movelets
      2. relevant subtrajectories
      3. spatio-temporal data analysis
      4. trajectory classification
      5. trajectory shapelets

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      April 9 - 13, 2018
      Pau, France

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      Overall Acceptance Rate 1,650 of 6,669 submissions, 25%

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      Cited By

      View all
      • (2024)Trajectory Mining and Routing: A Cross-Sectoral ApproachJournal of Marine Science and Engineering10.3390/jmse1201015712:1(157)Online publication date: 12-Jan-2024
      • (2024)Trajectory User Linking With Self Organizing TreesProceedings of the 1st ACM SIGSPATIAL International Workshop on Geospatial Anomaly Detection10.1145/3681765.3698450(28-31)Online publication date: 29-Oct-2024
      • (2024)Improving trajectory classification through Kramers–Moyal coefficientsAI Open10.1016/j.aiopen.2024.06.0015(87-93)Online publication date: 2024
      • (2024)UltraMovelets: Efficient Movelet Extraction for Multiple Aspect Trajectory ClassificationDatabase and Expert Systems Applications10.1007/978-3-031-68312-1_6(79-94)Online publication date: 26-Aug-2024
      • (2023)A real-time trajectory classification moduleProceedings of the 1st ACM SIGSPATIAL International Workshop on Methods for Enriched Mobility Data: Emerging issues and Ethical perspectives 202310.1145/3615885.3628005(11-14)Online publication date: 13-Nov-2023
      • (2023)Geolet: An Interpretable Model for Trajectory ClassificationAdvances in Intelligent Data Analysis XXI10.1007/978-3-031-30047-9_19(236-248)Online publication date: 1-Apr-2023
      • (2022)A Hierarchical Spatial-Temporal Embedding Method Based on Enhanced Trajectory Features for Ship Type ClassificationSensors10.3390/s2203071122:3(711)Online publication date: 18-Jan-2022
      • (2022)Differentiating geographic movement described in text documentsTransactions in GIS10.1111/tgis.1289326:2(923-948)Online publication date: 10-Jan-2022
      • (2022)Stat-DSM: Statistically Discriminative Sub-Trajectory Mining With Multiple Testing CorrectionIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2020.299434434:3(1477-1488)Online publication date: 1-Mar-2022
      • (2022)AUTOMATISE: Multiple Aspect Trajectory Data Mining Tool Library2022 23rd IEEE International Conference on Mobile Data Management (MDM)10.1109/MDM55031.2022.00060(282-285)Online publication date: Jun-2022
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