Aggregation and comparison of trajectories
Proceedings of the 10th ACM international symposium on Advances in geographic information systems
Design and Implementation of Multi-scale Databases
SSTD '01 Proceedings of the 7th International Symposium on Advances in Spatial and Temporal Databases
Multi-scale Classification of Moving Objects Trajectories
SSDBM '04 Proceedings of the 16th International Conference on Scientific and Statistical Database Management
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
A conceptual view on trajectories
Data & Knowledge Engineering
Mining interesting locations and travel sequences from GPS trajectories
Proceedings of the 18th international conference on World wide web
A method for predicting future location of mobile user for location-based services system
Computers and Industrial Engineering
A quantitative scale-setting approach for building multi-scale spatial databases
Computers & Geosciences
Mining user similarity from semantic trajectories
Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Location Based Social Networks
Smart itinerary recommendation based on user-generated GPS trajectories
UIC'10 Proceedings of the 7th international conference on Ubiquitous intelligence and computing
A trajectory correlation algorithm based on users' daily routines
Proceedings of the 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Computing with Spatial Trajectories
Computing with Spatial Trajectories
Clustering user trajectories to find patterns for social interaction applications
W2GIS'12 Proceedings of the 11th international conference on Web and Wireless Geographical Information Systems
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Social networking, and sophisticated wireless and positioning systems are fast developing and ever increasing technologies. Mobile social applications have the ability to increase the social connectivity by capturing automatically users' daily routines with Global Positioning System (GPS) receivers. These applications allow to record users' trajectories based on daily travel routes as well as to share experiences and interests among friends. However, there is always an increasing demand for providing an easy way to manipulate trajectory data, to generate and compare user profiles. Effective analysis of spatial trajectories has become an essential requirement to explore and understand the behavior of moving objects. In this paper, we highlight the importance of capturing users' daily routines in the form of trajectories in order to strengthen social connectivity. We also present the conceptual approach to multi-layer data representation in order to extract points of interest of correlated trajectories. Finally, we show how the data model could provide mobile social applications with direct support for trajectories at different abstraction levels.