Towards mobility data science (vision paper)

M Mokbel, M Sakr, L Xiong, A Züfle, J Almeida… - arXiv preprint arXiv …, 2023 - arxiv.org
Mobility data captures the locations of moving objects such as humans, animals, and cars.
With the availability of GPS-equipped mobile devices and other inexpensive location …

Diff-rntraj: A structure-aware diffusion model for road network-constrained trajectory generation

T Wei, Y Lin, S Guo, Y Lin, Y Huang… - … on Knowledge and …, 2024 - ieeexplore.ieee.org
Trajectory data is essential for various applications. However, publicly available trajectory
datasets remain limited in scale due to privacy concerns, which hinders the development of …

Multi-objective reinforcement learning approach for trip recommendation

L Chen, G Zhu, W Liang, Y Wang - Expert Systems with Applications, 2023 - Elsevier
Trip recommendation is an intelligent service that provides personalized itinerary plans for
tourists in unfamiliar cities. It aims to construct a series of ordered POIs that maximizes user …

Contrastive trajectory learning for tour recommendation

F Zhou, P Wang, X Xu, W Tai, G Trajcevski - ACM Transactions on …, 2021 - dl.acm.org
The main objective of Personalized Tour Recommendation (PTR) is to generate a sequence
of point-of-interest (POIs) for a particular tourist, according to the user-specific constraints …

Let's speak trajectories

M Musleh, MF Mokbel, S Abbar - … of the 30th International Conference on …, 2022 - dl.acm.org
Trajectory-based applications have acquired significant attention over the past decade with
the rising size of trajectory data generated by users. However, building trajectory-based …

Adversarial human trajectory learning for trip recommendation

Q Gao, F Zhou, K Zhang, F Zhang… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
The problem of trip recommendation has been extensively studied in recent years, by both
researchers and practitioners. However, one of its key aspects—understanding human …

Exploring the evolution, progress, and future of point-of-interest recommendation over location-based social network: a comprehensive review

M Acharya, KK Mohbey - GeoInformatica, 2024 - Springer
Location-based social networks (LBSNs) have bridged the gap between the virtual and real
worlds by allowing users to share their preferences and behaviors digitally. Point-of-Interest …

Kamel: A Scalable BERT-based System for Trajectory Imputation

M Musleh, MF Mokbel - Proceedings of the VLDB Endowment, 2023 - dl.acm.org
Numerous important applications rely on detailed trajectory data. Yet, unfortunately,
trajectory datasets are typically sparse with large spatial and temporal gaps between each …

Self-Explainable Next POI Recommendation

K Yang, Y Yang, Q Gao, T Zhong, Y Wang… - Proceedings of the 47th …, 2024 - dl.acm.org
Point-of-Interest (POI) recommendation involves predicting users' next preferred POI and is
becoming increasingly significant in location-based social networks. However, users are …

[HTML][HTML] Discovering the influence of facility distribution on lifestyle patterns in urban populations

C Fan, F Wu, A Mostafavi - Developments in the Built Environment, 2024 - Elsevier
The spatial structures of cities defined by population distribution, distribution of facilities, and
mobility have a significant impact on lifestyles of residents and their wellbeing. In this study …