  With the development of big data and artificial intelligence, the technology
of urban computing becomes more mature and widely used. In urban computing,
using GPS-based trajectory data to discover urban dense areas, extract similar
urban trajectories, predict urban traffic, and solve traffic congestion
problems are all important issues. This paper presents a GPS-based trajectory
pattern mining system called TPM. Firstly, the TPM can mine urban dense areas
via clustering the spatial-temporal data, and automatically generate
trajectories after the timing trajectory identification. Mainly, we propose a
method for trajectory similarity matching, and similar trajectories can be
extracted via the trajectory similarity matching in this system. The TPM can be
applied to the trajectory system equipped with the GPS device, such as the
vehicle trajectory, the bicycle trajectory, the electronic bracelet trajectory,
etc., to provide services for traffic navigation and journey recommendation.
Meantime, the system can provide support in the decision for urban resource
allocation, urban functional region identification, traffic congestion and so
on.
