Google Faculty Award 2017 on Analysing human mobility GPS trajectories

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2016 Results

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Corridor Learning Using Individual Trajectories

Nikolaos Zygouras, Dimitrios Gunopulos: Corridor Learning Using Individual Trajectories. In Mobile Data Management (MDM), 2018 19th IEEE International Conference on. IEEE. (to appear)
In this work, we proposed a pipelined approach for detecting a set of frequently accessed corridors from a vast collection of trajectories. Initially we applied a well known topic modelling technique to detect frequent sets of locations and then we derived the frequent corridors from the trajectories that accessed these locations.

Urban Travel Time Prediction using a Small Number of GPS-floating Cars

Li, Y., Gunopulos, D., Lu, C., & Guibas, L. (2017, November). Urban Travel Time Prediction using a Small Number of GPS Floating Cars. In Proceedings of the 25th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (p. 3). ACM.
While real-time collection of GPS trajectories from taxis and mobile users are common today, a practical solution for trajectory-based travel time prediction needs to be robust to the situation of only having access to a small number of active mobile probes. This paper presented an algorithm framework for predicting path travel time from GPS trajectories, under the scenario of 10-15 of GPS-floating cars and no trip labels.
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Discovering Corridors From GPS Trajectories

Zygouras, N., & Gunopulos, D. (2017, November). Discovering Corridors From GPS Trajectories. In Proceedings of the 25th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (p. 61). ACM.
In this work a pipelined approach is proposed for detecting a set of frequently accessed paths, named as corridors, from a vast collection of trajectories. Initially we applied a well known topic modelling technique to detect frequent sets of locations and then we derived frequent paths at these locations. Our initial experimental results demonstrate the ability of our approach to summarize a large collection of trajectories to a few number of frequently accessed paths. The detection of such corridors abstracts the complex trajectories and returns the major movement patterns.
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