Algorithms on strings, trees, and sequences: computer science and computational biology
Algorithms on strings, trees, and sequences: computer science and computational biology
A User-Centered Location Model
Personal and Ubiquitous Computing
Similarity between Event Types in Sequences
DaWaK '99 Proceedings of the First International Conference on Data Warehousing and Knowledge Discovery
Using GPS to learn significant locations and predict movement across multiple users
Personal and Ubiquitous Computing
Route profiling: putting context to work
Proceedings of the 2004 ACM symposium on Applied computing
Extracting places from traces of locations
Proceedings of the 2nd ACM international workshop on Wireless mobile applications and services on WLAN hotspots
ContextPhone: A Prototyping Platform for Context-Aware Mobile Applications
IEEE Pervasive Computing
Density estimation for out-of-range events on personal mobile devices
Proceedings of the 1st ACM SIGMOBILE workshop on Mobility models
Wideband powerline positioning for indoor localization
UbiComp '08 Proceedings of the 10th international conference on Ubiquitous computing
Predicting the location of mobile users: a machine learning approach
Proceedings of the 2009 international conference on Pervasive services
AP and MN-centric mobility prediction: a comparative study based on wireless traces
NETWORKING'07 Proceedings of the 6th international IFIP-TC6 conference on Ad Hoc and sensor networks, wireless networks, next generation internet
Probabilistic context prediction using time-inferred multiple pattern networks
Proceedings of the 2010 ACM Symposium on Applied Computing
Predicting mobility events on personal devices
Pervasive and Mobile Computing
Mobility profiler: A framework for discovering mobility profiles of cell phone users
Pervasive and Mobile Computing
A personal route prediction system based on trajectory data mining
Information Sciences: an International Journal
On Context Modelling in Systems and Applications Development
Proceedings of the 2011 conference on Information Modelling and Knowledge Bases XXII
Mining individual mobility patterns from mobile phone data
Proceedings of the 2011 international workshop on Trajectory data mining and analysis
Getting closer: an empirical investigation of the proximity of user to their smart phones
Proceedings of the 13th international conference on Ubiquitous computing
UbiComp'06 Proceedings of the 8th international conference on Ubiquitous Computing
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Location-awareness and prediction of future locations is an important problem in pervasive and mobile computing. In cellular systems (e.g., GSM) the serving cell is easily available as an indication of the user location, without any additional hardware or network services. With this location data and other context variables we can determine places that are important to the user, such as work and home. We devise online algorithms that learn routes between important locations and predict the next location when the user is moving. We incrementally build clusters of cell sequences to represent physical routes. Predictions are based on destination probabilities derived from these clusters. Other context variables such as the current time can be integrated into the model. We evaluate the model with real location data, and show that it achieves good prediction accuracy with relatively little memory, making the algorithms suitable for online use in mobile environments.