Predicting future locations with hidden Markov models

By Wesley Mathew, Ruben Raposo, Bruno Martins. Ubiquitous Computing, 2012

400 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Computer Vision and Pattern Recognition, Transportation

View Paper: https://www.semanticscholar.org/paper/aff0e3935c090e5cd65f9d86b00eb778149925bd

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

1. Yong Li

In Computer Vision and Pattern Recognition

1. Fanchao Meng
2. Ang Guo
3. Yong Li
4. Funing Sun
5. Jie Feng
6. Depeng Jin

In Transportation

1. Yong Li
2. Depeng Jin

Citations in the corpus

• DeepMove: Predicting Human Mobility with Attentional Recurrent Networks (2018, methodology): “[22] cluster the locations from the trajectories and then train a Hidden Markov Model for each user.”