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Learning Citywide Patterns of Life from Trajectory Monitoring. (arXiv:2206.15352v1 [cs.LG])
July 1, 2022, 1:10 a.m. | Mark Tenzer, Zeeshan Rasheed, Khurram Shafique
cs.LG updates on arXiv.org arxiv.org
The recent proliferation of real-world human mobility datasets has catalyzed
geospatial and transportation research in trajectory prediction, demand
forecasting, travel time estimation, and anomaly detection. However, these
datasets also enable, more broadly, a descriptive analysis of intricate systems
of human mobility. We formally define patterns of life analysis as a natural,
explainable extension of online unsupervised anomaly detection, where we not
only monitor a data stream for anomalies but also explicitly extract normal
patterns over time. To learn patterns of …
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