The importance of analysing moving object data has increased significantly due to the increased acceptance of context aware devices such as Smartphones, GPS connected gadgets etc. Broad use of wireless context aware devices has accelerated the generation of mobility data in various formats.The vital component of moving object data constitutes of geographical coordinates and time. The analysis of space time points in mobility data gives deep knowledge about the movement pattern of the object. Because of the presence of rich semantic aspects in the moving object data, the mining of context related data requires special methods and attention. There are less number of reported works that primarily focuses on the spatial and temporal behavior of moving objects. This research paper concentrate on the methods of extracting Points of Interests from the moving object trajectories by considering its Spatial and Temporal aspects so as to mine useful knowledge from it. Along with the explicit mobility data the method also considers semantic attributes underlined in the travel trajectory.

Location Based Systems, Moving Objects Clustering, Semantic Trajectory, Spatio Temporal Data mining Clustering

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