discovering human places of interest from multimodal mobile phone data
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Discovering Human Places of Interest from Multimodal Mobile Phone Data
2014/11/4 (Tue.)�Chang Wei-Yuan @ MakeLab Group Meeting
Raul Montoliu, Daniel Gatica-Perez �MUM‘13
+Outline
n Introduction �
n Definition �
n Method �n Operation modes �n Time-based Clustering �n Grid-based Clustering �
n Experiment �
n Conclusion �
n Thought
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+Outline
n Introduction �
n Definition �
n Method �n Operation modes �n Time-based Clustering �n Grid-based Clustering �
n Experiment �
n Conclusion �
n Thought
3
+Outline
n Introduction �
n Definition �
n Method �n Operation modes �n Time-based Clustering �n Grid-based Clustering �
n Experiment �
n Conclusion �
n Thought
6
+Definition
n Location Point �n a measurement about the location of a user�n e.g. ([46:6N; 6:5E], [16:34:57])�
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+Definition
n Stay Point �n a geographic region in which the user stayed
for a while �n e.g. ([46:6N; 6:5E], [16:30:00], [17:54:34])�
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+Definition
n Stay Region �n a cluster of stay points with the same
semantic meaning �n e.g. ([46:6N; 6:5E]; [46:595N;-46:599N];
[6:498E; 6:502E])
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+Outline
n Introduction �
n Definition �
n Method �n Operation modes �n Time-based Clustering �n Grid-based Clustering �
n Experiment �
n Conclusion �
n Thought
10
+Outline
n Introduction �
n Definition �
n Method �n Operation modes �n Time-based Clustering �n Grid-based Clustering �
n Experiment �
n Conclusion �
n Thought
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+Operation modes
n Multimodal Mobile Phone Data�
n Wifi-map Mode �n a map of geo-referenced Wifi APs �
n Static Mode �
n GPS Mode �
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+Outline
n Introduction �
n Definition �
n Method �n Operation modes �n Time-based Clustering �n Grid-based Clustering �
n Experiment �
n Conclusion �
n Thought
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+Time-based Clustering
n Location Point = lp = (p1, p2, …, pN)�n Pi = (lat, long, T) �n obtained from the multimodal sensor�
n Stay points = lsp = (sp1, sp2, …, spM)�n spi = (lat, long, Tstart, Tend)�
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+Time-based Clustering
n SpaceDistance(ps; pe) < Dmax �
n TimeDifference(ps; pe) > Tmin �
n TimeDifference(pk; pk+1) < Tmax �n k ∈ [s, e]
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+Outline
n Introduction �
n Definition �
n Method �n Operation modes �n Time-based Clustering �n Grid-based Clustering �
n Experiment �
n Conclusion �
n Thought
18
+Outline
n Introduction �
n Definition �
n Method �n Operation modes �n Time-based Clustering �n Grid-based Clustering �
n Experiment �
n Conclusion �
n Thought
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+Extracting location points
GPS 4%
Wifi Map 35%
Static 24%
No location
37%
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n approximately for 63% of the day it is possible to estimate the location of a user
+Comparative results on place of�interest discovering
n Evaluation System�n Discovered �n Remembered �n Missed �n Correct �n Forgotten �n False
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+Comparative results on place of�interest discovering
n Evaluation System�n Discovered �n Remembered �n Missed �n Correct ↑�n Forgotten ↑�n False
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+Outline
n Introduction �
n Definition �
n Method �n Operation modes �n Time-based Clustering �n Grid-based Clustering �
n Experiment �
n Conclusion �
n Thought
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+Conclusion
n Thanks to the use of this framework, it is possible to obtain location data for 63% of the day in real life. �
n This approach is multimodal since location information is obtained from multiple sensor.
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+Outline
n Introduction �
n Definition �
n Method �n Operation modes �n Time-based Clustering �n Grid-based Clustering �
n Experiment �
n Conclusion �
n Thought
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