Discovering Similar Multidimensional Trajectories

ICDE, San Jose, CA, 2002Discovering Similar Multidimensional TrajectoriesMichail VlachosGeorge KolliosDimitrios GunopulosUC RiversideBoston UniversityUC RiversideOutlineIntroductionSimilarity MeasuresCompute the SimilarityIndexing TrajectoriesExperimental EvaluationRelated WorkConclusionIntroductionThe trajectory of a moving object is typically modeled as a sequence of consecutive locations in a multidimensional Euclidean spaceAn appropriate and efficient model for defining the similarity for trajectory data will be very important for the quality of the data analysis tasks.Examples of 2D trajectories

Hierarchical clustering of 2D series

(displayed as 1D for clariry)Similarity MeasuresLet A and B be two trajectories of moving objects with size n and m respectively, where A = ((ax,1 , ay,1),,(ax,n , ay,n)) and B = ((bx,1 , by,1),,(bx,m , by,m)). For a trajectory A, let Head(A) be the sequence Head(A) = ((ax,1 , ay,1),,(ax,n-1 , ay,n-1))Denition 1Given an integer and a real number 0 <