Attentional Markov model for human mobility prediction

H Wang, Y Li, D Jin, Z Han - IEEE Journal on Selected Areas in …, 2021 - ieeexplore.ieee.org
Accurate human mobility prediction is important for many applications in wireless networks,
including intelligent content caching and prefetching, network optimization, etc. However …

Group-based recurrent neural network for human mobility prediction

S Ke, M Xie, H Zhu, Z Cao - Neural Computing and Applications, 2022 - Springer
Human mobility prediction is of great significance for analyzing the check-in data generated
by location-based applications. Compared with classical prediction methods, recently …

[PDF][PDF] MSSRM: A multi-embedding based self-attention spatio-temporal recurrent model for human mobility prediction

S Wen, X Zhang, R Cao, B Li, Y Li - HCIS, 2021 - hcisj.com
Human mobility affects many aspects of an urban area, including spatial structure, temporal
connectivity, even response to epidemics. Prediction of human mobility is of great …

Human mobility prediction using sparse trajectory data

H Wang, S Zeng, Y Li, P Zhang… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Human mobility prediction techniques are instrumental for many important applications
including service management and city planning. Previous work looks at the inherent …

Predictability and prediction of human mobility based on application-collected location data

H Wang, S Zeng, Y Li, D Jin - IEEE Transactions on Mobile …, 2020 - ieeexplore.ieee.org
In the modern information society, analysis of human mobility becomes increasingly
essential in various areas such as city planning and resource management. With users' …

A hybrid Markov-based model for human mobility prediction

Y Qiao, Z Si, Y Zhang, FB Abdesslem, X Zhang, J Yang - Neurocomputing, 2018 - Elsevier
Human mobility behavior is far from random, and its indicators follow non-Gaussian
distributions. Predicting human mobility has the potential to enhance location-based …

Star: A concise deep learning framework for citywide human mobility prediction

H Wang, H Su - 2019 20th IEEE International Conference on …, 2019 - ieeexplore.ieee.org
Human mobility forecasting in a city is of utmost importance to transportation and public
safety, but with the process of urbanization and the generation of big data, intensive …

Predicting human mobility via graph convolutional dual-attentive networks

W Dang, H Wang, S Pan, P Zhang, C Zhou… - Proceedings of the …, 2022 - dl.acm.org
Human mobility prediction is of great importance for various applications such as smart
transportation and personalized recommender systems. Although many traditional pattern …

Crowdsourced mobility prediction based on spatio-temporal contexts

H Pang, P Wang, L Gao, M Tang… - 2016 IEEE …, 2016 - ieeexplore.ieee.org
Accurate mobility prediction is becoming increasingly important in human behavior
research, mainly due to many location-based applications such as mobile social networks …

Predicting human mobility with semantic motivation via multi-task attentional recurrent networks

J Feng, Y Li, Z Yang, Q Qiu, D Jin - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Human mobility prediction is of great importance for a wide spectrum of location-based
applications. However, predicting mobility is not trivial because of four challenges: 1) the …