Name
Abstract | ||
|---|---|---|
Accurate human mobility prediction is important for many applications in wireless networks, including intelligent content caching and prefetching, network optimization, etc. However, modeling mobility patterns has been a challenging problem due to the complicated human mobility patterns influenced by the long-term correlation with historical trajectories and context information, and the long time ... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/JSAC.2021.3078499 | IEEE Journal on Selected Areas in Communications |
Keywords | DocType | Volume |
Hidden Markov models,Context modeling,Computational modeling,Predictive models,Trajectory,Markov processes,Correlation | Journal | 39 |
Issue | ISSN | Citations |
7 | 0733-8716 | 2 |
PageRank | References | Authors |
0.36 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Huandong Wang | 1 | 114 | 14.20 |
| Yong Li | 2 | 2972 | 218.82 |
| Depeng Jin | 3 | 2177 | 154.29 |
| Zhu Han | 4 | 11215 | 760.71 |