Optimal suffix tree construction with large alphabets
FOCS '97 Proceedings of the 38th Annual Symposium on Foundations of Computer Science
Using GPS to learn significant locations and predict movement across multiple users
Personal and Ubiquitous Computing
The Wisdom of Crowds
A stochastic memoizer for sequence data
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Maximum entropy inverse reinforcement learning
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 3
Hidden Markov map matching through noise and sparseness
Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Lossless Compression Based on the Sequence Memoizer
DCC '10 Proceedings of the 2010 Data Compression Conference
The Journal of Machine Learning Research
Improvement of Li-Hwang's biometrics-based remote user authentication scheme using smart cards
WSEAS TRANSACTIONS on COMMUNICATIONS
Reducing Uncertainty of Low-Sampling-Rate Trajectories
ICDE '12 Proceedings of the 2012 IEEE 28th International Conference on Data Engineering
| Hi-index | 0.00 |
Route prediction is important to analyzing and understanding the route patterns and behavior of traffic crowds. Its objective is to predict the most likely or "popular" route of road segments from a given point in a road network. This paper presents a hierarchical Bayesian non-parametric approach to efficient and scalable route prediction that can harness the wisdom of crowds of route planning agents by aggregating their sequential routes of possibly varying lengths and origin-destination pairs. In particular, our approach has the advantages of (a) not requiring a Markov assumption to be imposed and (b) generalizing well with sparse data, thus resulting in significantly improved prediction accuracy, as demonstrated empirically using real-world taxi route data. We also show two practical applications of our route prediction algorithm: predictive taxi ranking and route recommendation.