Analysis of User Similarity Measures Using GPS Trajectories

The emergent research in mobile and communication technology and easy availability of GPS data have unlocked the way for new research areas of Moving Object Databases. MODs deal with geometries which changes over time. his data represents the motion history of moving objects which is known as Mobility Profiles. Use of sensor and GPS technologies have produced a sheer volume of trajectory data. The growing industry of location-based services has gathered a massive collection of users' location trajectories. User' has access to these collections of huge trajectory dataset. These spatio-temporal datasets stores users' movement behavior. Along with spatiotemporal features, there is need to enrich basic trajectories with other parameters to make its movement more meaningful. This research area has exposed numerous opportunities for researchers along with challenges related to it. One of the fundamental task related to spatio temporal datasets is to find similarity in between various trajectories. Which, is a crucial part in mining trajectories which can be further used in predictions systems, recommendation systems, clustering, classification etc. In this paper, we have reviewed various similarity measures and calculated most similar users using few basic trajectory similarity measures. We have explored and enriched users' trajectories with few significant parameters.