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Clustering Algorithm for Network Constraint Trajectories
[chapter]
Lecture Notes in Geoinformation and Cartography
Spatial data mining is an active topic in spatial databases. This paper proposes a new clustering method for moving object trajectories databases. It applies specifically to trajectories that only lie on a predefined network. The proposed algorithm (NETSCAN) is inspired from the wellknown density based algorithms. However, it takes advantage of the network constraint to estimate the object density. Indeed, NETSCAN first computes dense paths in the network based on the moving object count, then,
doi:10.1007/978-3-540-68566-1_36
fatcat:bwdy3zmlxjggdmrvetm23nhkfq