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Individual movements and geographical data mining. Clustering algorithms for highlighting hotspots in personal navigation routes.

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Beniamino Murgante
Beniamino Murgante

Individual movements and geographical data mining. Clustering algorithms for highlighting hotspots in personal navigation routes. Giuseppe Borruso, Gabriella Schoier - University of Trieste

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Individual movements and geographical data mining. Clustering algorithms for highlighting hotspots in personal navigation routes. Giuseppe Borruso, Gabriella Schoier Department of Economic, Business, Mathematic and Statistic Sciences - DEAMS, University of Trieste, Via Valerio, 4/1, 34127 Trieste, Italy {gabriella.schoier,giuseppe.borruso}@econ.units.it Geographical Analysis, Urban Modeling, Spatial Statistics GEOG-AN-MOD 11
Introduction ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Geographical Data Mining ,[object Object],[object Object],[object Object],[object Object],[object Object]
Spatial Clustering Algorithms ,[object Object],[object Object],[object Object],[object Object]
Kernel Density Estimation ,[object Object],[object Object],Gatrell A., Bailey T, Diggle P., Rowlingson B. (1996): “Spatial Point Pattern Analysis and its Application in Geographical Epidemiology”. Transactions of the Institute of British Geographers 21: 256-74. Study Region R Event s i Location s Kernel k( ) Bandwidth τ
Kernel Density Estimation ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Some Comparisons between DBSCAN and KDE ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
The Data and the Study Area ,[object Object],[object Object],[object Object],[object Object]
A data sample: October data (5, 6, 7, 8, 11, 12)
Anticipation – density analysis on different routes & days
A data sample: October data (5, 6, 7, 8, 11, 12) Sample POIs University campus Gym Home (2) Home (1) Nursery
[object Object],[object Object],[object Object],University campus Home (1) Nursery
The Analysis ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],1 059 GPS points collected on 1° September 2010 (Home – Nursery journey)
Results from DBSCAN (right) and KDE (left)
The results ,[object Object],[object Object],[object Object],[object Object],[object Object]
 
 
University campus – entrance and bus stop
Junction – state roads
Nursery – end of the journey
Conclusions and further development ,[object Object],[object Object],[object Object],[object Object],[object Object]
Thank you for your attention! Questions?

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Individual movements and geographical data mining. Clustering algorithms for highlighting hotspots in personal navigation routes.

  • 1. Individual movements and geographical data mining. Clustering algorithms for highlighting hotspots in personal navigation routes. Giuseppe Borruso, Gabriella Schoier Department of Economic, Business, Mathematic and Statistic Sciences - DEAMS, University of Trieste, Via Valerio, 4/1, 34127 Trieste, Italy {gabriella.schoier,giuseppe.borruso}@econ.units.it Geographical Analysis, Urban Modeling, Spatial Statistics GEOG-AN-MOD 11
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  • 9. A data sample: October data (5, 6, 7, 8, 11, 12)
  • 10. Anticipation – density analysis on different routes & days
  • 11. A data sample: October data (5, 6, 7, 8, 11, 12) Sample POIs University campus Gym Home (2) Home (1) Nursery
  • 12.
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  • 14. Results from DBSCAN (right) and KDE (left)
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  • 18. University campus – entrance and bus stop
  • 20. Nursery – end of the journey
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  • 22. Thank you for your attention! Questions?