Adaptive user movement prediction for advanced location-aware services

Location-based services are services that provide some information related to the specific location. Location is usually defined as basic, geographical location. However, this kind of information can be upgraded with additional knowledge about user context, such as knowledge about movement habits. The upgrade of basic location information with other contextual information is the key for enabling advanced location-aware services. In this work we propose user movement prediction system as an upgrade of basic location information. The proposed system is based on statistical analysis of user movement and has the ability to adapt to eventual changes in user movement behaviour.

[1]  Hassan A. Karimi,et al.  A predictive location model for location-based services , 2003, GIS '03.

[2]  Alex Pentland,et al.  Reality mining: sensing complex social systems , 2006, Personal and Ubiquitous Computing.

[3]  Alejandro Quintero A user pattern learning strategy for managing users' mobility in UMTS networks , 2005, IEEE Transactions on Mobile Computing.

[4]  Nabanita Das,et al.  Mobile User Tracking Using A Hybrid Neural Network , 2005, Wirel. Networks.

[5]  P.R.L. Gondim,et al.  Genetic algorithms and the location area partitioning problem in cellular networks , 1996, Proceedings of Vehicular Technology Conference - VTC.

[6]  Chris Schmandt,et al.  Location-Aware Information Delivery with ComMotion , 2000, HUC.

[7]  Thad Starner,et al.  Learning Significant Locations and Predicting User Movement with GPS , 2002, Proceedings. Sixth International Symposium on Wearable Computers,.

[8]  I. Lovrek,et al.  Predicting user movement for advanced location-aware services , 2007, 2007 15th International Conference on Software, Telecommunications and Computer Networks.

[9]  Vjekoslav Sinkovic,et al.  Mobility Management for Personal Agents in the All-mobile Network , 2004, KES.