Density-based trajectory segmentation: the MigrO framework

Overview. MigrO is a platform for the extraction of individual mobility patterns from GPS trajectories, relying on the notion of stay region. A stay region is an 'attractive' area where the moving object resides for a period, possibly experiencing arbitrarily long periods of absence, before moving to a more attractive stay region. The core component is the SeqScan algorithm. MigrO is developed as plug-in for QGIS.

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Publications

  • F. Hachem, M.L. Damiani. Periodic stops discovery through density-based trajectory segmentation. Demo. ACM SIGSPATIAL (2018)
  • https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/JCICNL. Replication Data for: Cluster-based trajectory segmentation with local noise.
  • M.L. Damiani, F. Hachem, H. Issa et al. (2018). Cluster-based trajectory segmentation with local noise (2018). Data Mining and Knowledge Discovery.
  • M.L. Damiani, F. Hachem (2017). Segmentation techniques for the summarization of individual mobility data. Wiley Interdisc. Rew.: Data Mining and Knowledge Discovery 7(6).
  • H. Hachem, M.L. Damiani, H.Issa (2017). Discovering Gatherings Based on Individual Mobility Patterns: Challenges and Direction. IEEE ICDM Workshops. 2017
  • H. Issa (2017). Spatio-textual trajectories: models and applications. PhD Thesis
  • M.L. Damiani, H. Issa, G. Fotino, M. Heurich, F. Cagnacci (2016). Introducing 'presence' and 'stationarity index' to study partial migration patterns: an application of a spatio-temporal clustering technique. IJGIS, International Journal of Geographical Information Science, Vol. 30, N. 5, pp.907–928
  • M.L. Damiani, H. Issa, G. Fotino, F. Hachem, N. Ranc, F. Cagnacci (2015). MigrO: a plug–in for the analysis of individual mobility behavior based on the stay region model. ACM SIGSPATIAL'15. Best demo award
  • M.L. Damiani, H. Issa, F. Cagnacci (2014). Extracting stay regions with uncertain boundaries from GPS Trajectories: a case study in animal ecology. ACM SIGSPATIAL ’14.
start/clustering.txt · Last modified: 2018/10/05 14:58 by Maria Luisa Damiani
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