Clustering the Movement of Trajectory Based Data

Abstract: This paper group the trajectories objects of moving data. Our observation that develops the new algorithms that manage Minimum Description Length (MDL). This paper based on k-nearest algorithm with LCSS model and dimensional Euclidean. Our algorithm consists of two parts that is partitioning and grouping phase. Experimental result searching the minimum distance by using MOTRACLUS algorithm and analysis the sub-trajectories and real-trajectories. The experimental analysis gives moving object of trajectory animals.

Keywords: Data mining, Density based cluster, Trajectory algorithm, Framework grouped, Partition and group work.