Optimal prefetching via data compression
Journal of the ACM (JACM)
Learning Significant Locations and Predicting User Movement with GPS
ISWC '02 Proceedings of the 6th IEEE International Symposium on Wearable Computers
Discovering personal gazetteers: an interactive clustering approach
Proceedings of the 12th annual ACM international workshop on Geographic information systems
On the complexity of optimal K-anonymity
PODS '04 Proceedings of the twenty-third ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Evaluating Next-Cell Predictors with Extensive Wi-Fi Mobility Data
IEEE Transactions on Mobile Computing
Understanding mobility based on GPS data
UbiComp '08 Proceedings of the 10th international conference on Ubiquitous computing
Mining user similarity from semantic trajectories
Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Location Based Social Networks
Show Me How You Move and I Will Tell You Who You Are
Transactions on Data Privacy
Pedestrian-movement prediction based on mixed Markov-chain model
Proceedings of the 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Semantic trajectory mining for location prediction
Proceedings of the 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Comparison of different methods for next location prediction
Euro-Par'06 Proceedings of the 12th international conference on Parallel Processing
Predestination: inferring destinations from partial trajectories
UbiComp'06 Proceedings of the 8th international conference on Ubiquitous Computing
Predicting future locations with hidden Markov models
Proceedings of the 2012 ACM Conference on Ubiquitous Computing
Proceedings of the First ACM SIGSPATIAL International Workshop on Mobile Geographic Information Systems
Extrapolating sparse large-scale GPS traces for contact evaluation
Proceedings of the 5th ACM workshop on HotPlanet
Personalized point-of-interest recommendation by mining users' preference transition
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
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In this paper, we address the issue of predicting the next location of an individual based on the observations of his mobility behavior over some period of time and the recent locations that he has visited. This work has several potential applications such as the evaluation of geo-privacy mechanisms, the development of location-based services anticipating the next movement of a user and the design of location-aware proactive resource migration. In a nutshell, we extend a mobility model called Mobility Markov Chain (MMC) in order to incorporate the n previous visited locations and we develop a novel algorithm for next location prediction based on this mobility model that we coined as n-MMC. The evaluation of the efficiency of our algorithm on three different datasets demonstrates an accuracy for the prediction of the next location in the range of 70% to 95% as soon as n = 2.