Deep learning for spatio-temporal data mining: A survey
With the fast development of various positioning techniques such as Global Position System
(GPS), mobile devices and remote sensing, spatio-temporal data has become increasingly …
(GPS), mobile devices and remote sensing, spatio-temporal data has become increasingly …
Deep learning for trajectory data management and mining: A survey and beyond
Trajectory computing is a pivotal domain encompassing trajectory data management and
mining, garnering widespread attention due to its crucial role in various practical …
mining, garnering widespread attention due to its crucial role in various practical …
MobTCast: Leveraging auxiliary trajectory forecasting for human mobility prediction
Human mobility prediction is a core functionality in many location-based services and
applications. However, due to the sparsity of mobility data, it is not an easy task to predict …
applications. However, due to the sparsity of mobility data, it is not an easy task to predict …
Adversarial point-of-interest recommendation
Point-of-interest (POI) recommendation is essential to a variety of services for both users and
business. An extensive number of models have been developed to improve the …
business. An extensive number of models have been developed to improve the …
Drive2friends: Inferring social relationships from individual vehicle mobility data
The number of vehicles has increased year by year, especially individual vehicles. In
addition to meeting basic transportation needs, vehicles are expected to serve varied …
addition to meeting basic transportation needs, vehicles are expected to serve varied …
Urban flow prediction with spatial–temporal neural ODEs
With the recent advances in deep learning, data-driven methods have shown compelling
performance in various application domains enabling the Smart Cities paradigm …
performance in various application domains enabling the Smart Cities paradigm …
Dual-grained human mobility learning for location-aware trip recommendation with spatial–temporal graph knowledge fusion
Trip recommendation is a popular and significant location-aware service that can help
visitors make more accurate travel plans. Its principal purpose is to provide a sequence of …
visitors make more accurate travel plans. Its principal purpose is to provide a sequence of …
Large-scale vehicle trajectory reconstruction with camera sensing network
Vehicle trajectories provide essential information to understand the urban mobility and
benefit a wide range of urban applications. State-of-the-art solutions for vehicle sensing may …
benefit a wide range of urban applications. State-of-the-art solutions for vehicle sensing may …
Contextual spatio-temporal graph representation learning for reinforced human mobility mining
The rapid development of location-based services spurred a large number of user-centric
applications. Particularly, an interesting topic has attracted the attention of researchers that …
applications. Particularly, an interesting topic has attracted the attention of researchers that …
[HTML][HTML] Towards explainable traffic flow prediction with large language models
Traffic forecasting is crucial for intelligent transportation systems. It has experienced
significant advancements thanks to the power of deep learning in capturing latent patterns of …
significant advancements thanks to the power of deep learning in capturing latent patterns of …