Co-Clustering Network-Constrained Trajectory Data

@inproceedings{Mahrsi2013CoClusteringNT,
  title={Co-Clustering Network-Constrained Trajectory Data},
  author={Mohamed Khalil El Mahrsi and Romain Guigour{\`e}s and Fabrice Rossi and Marc Boull{\'e}},
  booktitle={EGC},
  year={2013}
}
Recently, clustering moving object trajectories kept gaining interest from both the data mining and machine learning communities. This problem, however, was studied mainly and extensively in the setting where moving objects can move freely on the euclidean space. In this paper, we study the problem of clustering trajectories of vehicles whose movement is restricted by the underlying road network. We model relations between these trajectories and road segments as a bipartite graph and we try to… 
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4 Citations
Background Citations
3
Methods Citations
2

4 Citations

Mining frequency-based sequential trajectory co-clusters
TLDR
This work proposes a new trajectory co-clustering method that simultaneously clusters the trajectories and their elements taking into account the order in which they appear, and uses the element frequency to identify candidate co- clusters.
Recognizing Network Trip Patterns Using a Spatio-Temporal Vehicle Trajectory Clustering Algorithm
TLDR
The proposed algorithm ST-TOPOSCAN is designed to consider both temporal and spatial information in trajectories and adopts the time-dependent shortest-path distance measurement and takes advantage of topological relations of a predefined network to discover the shared sub-paths among trajectory and construct the clusters.
14 11 0 v 1 [ cs . L G ] 2 7 O ct 2 02 1 Mining frequency-based sequential trajectory co-clusters
TLDR
This work proposes a new trajectory co-clustering method that simultaneously clusters the trajectories and their elements taking into account the order in which they appear, and uses the element frequency to identify candidate co- clusters.
Data mining-based model for motion target trajectory prediction

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