Knowledge Discovery of Trajectories Under Multi-scale Environment

For the purpose of mining distributions and movement patterns of moving objects at different levels of details,this paper presents a semantic-based multi-scale trajectory modeling and knowledge discovery method.Two matrixes are used to represent the multi-scale trajectory.A matrix based frequent item-set mining algorithm is developed to discover the association-rules in trajectory database.Experiments show that the approach is correct and feasible.