Towards mobility data science (vision paper)
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 …
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
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 …
datasets remain limited in scale due to privacy concerns, which hinders the development of …
Multi-objective reinforcement learning approach for trip recommendation
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 …
tourists in unfamiliar cities. It aims to construct a series of ordered POIs that maximizes user …
Contrastive trajectory learning for tour recommendation
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 …
of point-of-interest (POIs) for a particular tourist, according to the user-specific constraints …
Let's speak trajectories
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 …
the rising size of trajectory data generated by users. However, building trajectory-based …
Adversarial human trajectory learning for trip recommendation
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 …
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
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 …
worlds by allowing users to share their preferences and behaviors digitally. Point-of-Interest …
Kamel: A Scalable BERT-based System for Trajectory Imputation
Numerous important applications rely on detailed trajectory data. Yet, unfortunately,
trajectory datasets are typically sparse with large spatial and temporal gaps between each …
trajectory datasets are typically sparse with large spatial and temporal gaps between each …
Self-Explainable Next POI Recommendation
Point-of-Interest (POI) recommendation involves predicting users' next preferred POI and is
becoming increasingly significant in location-based social networks. However, users are …
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
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 …
mobility have a significant impact on lifestyles of residents and their wellbeing. In this study …