Trajectory Clustering Approaches for Location Aware Services

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Lokesh Kumar Sharma
Sanjiv Kumar Shukla, Sourabh Rungta


Modern Geographic Information Systems (GIS) can handle dynamically moving objects. It is becoming possible to record data about the movement of people and objects at a large scale. Location Aware Service (LAS) is service as the application of which the service and information provided is determined by the user location. In this study, we consider the trajectory data to identify the important location for services. Clustering algorithms for these trajectory objects provide new and helpful information, e.g. location aware services, traffic jam detection and identifying the interest place. Trajectory data contains uncertain positional information. In this paper, DBSCAN, k-means and Fuzzy C Mean clustering approach for trajectory data is implemented and tested and in real dataset. The results are reported in this study.

Keywords: Location Aware Services; Trajectory Cluster; DBSCAN; Fuzzy C-Means; k-Means.


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