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ComeTogether: Discovering Communities of Places in Mobility Data
2 references·1 citing·10 second hop
ComeTogether: Discovering Communities of Places in Mobility Data (2012)ComeTogether: Discovering Communities of …Learning Location Correlation from GPS Trajectories (2010)Learning Location Correlation…Mobility, Data Mining and Privacy: Geographic Knowledge Discovery (2008)Mobility, Data Mining and Pri…Retrieving Points of Interest from Human Systematic Movements (2015)Retrieving Points of Interest…Reality mining: sensing complex social systems (2005)Understanding individual human mobility patterns (2008)Understanding mobility based on GPS data (2008)Clustering Users by Their Mobility Behavioral Patterns (2019)A BiLSTM-CNN model for predicting users’ next locations based on geotagged social media (2020)Capturing urban recreational hotspots from GPS data: A new framework in the lens of spatial heterogeneity (2023)Redrawing the Map of Great Britain from a Network of Human Interactions (2010)From social data mining to forecasting socio-economic crises (2011)Methods for deriving and calibrating privacy-preserving heat maps from mobile sports tracking application data (2015)Big Data for transportation and mobility: recent advances, trends and challenges (2018)
this work references cited by second hop

References

  • 2008Mobility, Data Mining and Privacy: Geographic Knowledge Discovery195 cited
  • 2010Learning Location Correlation from GPS Trajectories76 cited

Cited by

  • 2015Retrieving Points of Interest from Human Systematic Movements7 cited

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