Multivariate correlation-aware spatio-temporal graph convolutional networks for multi-scale traffic prediction
Traffic flow prediction based on vehicle trajectories collected from the installed GPS devices
is critically important to Intelligent Transportation Systems (ITS). One limitation of existing …
is critically important to Intelligent Transportation Systems (ITS). One limitation of existing …
Stochastic origin-destination matrix forecasting using dual-stage graph convolutional, recurrent neural networks
Origin-destination (OD) matrices are used widely in transportation and logistics to record the
travel cost (eg, travel speed or greenhouse gas emission) between pairs of OD regions …
travel cost (eg, travel speed or greenhouse gas emission) between pairs of OD regions …
Location-and keyword-based querying of geo-textual data: a survey
With the broad adoption of mobile devices, notably smartphones, keyword-based search for
content has seen increasing use by mobile users, who are often interested in content related …
content has seen increasing use by mobile users, who are often interested in content related …
Multimodal named entity recognition with image attributes and image knowledge
Multimodal named entity extraction is an emerging task which uses both textual and visual
information to detect named entities and identify their entity types. The existing efforts are …
information to detect named entities and identify their entity types. The existing efforts are …
Fast query decomposition for batch shortest path processing in road networks
Shortest path query is a fundamental operation in various location-based services (LBS) and
most of them process queries on the server-side. As the business expands, scalability …
most of them process queries on the server-side. As the business expands, scalability …
Semi-supervised clustering with deep metric learning and graph embedding
As a common technology in social network, clustering has attracted lots of research interest
due to its high performance, and many clustering methods have been presented. The most …
due to its high performance, and many clustering methods have been presented. The most …
Go slow to go fast: minimal on-road time route scheduling with parking facilities using historical trajectory
For thousands of years, people have been innovating new technologies to make their travel
faster, the latest of which is GPS technology that is used by millions of drivers every day. The …
faster, the latest of which is GPS technology that is used by millions of drivers every day. The …
Minimal on-road time route scheduling on time-dependent graphs
On time-dependent graphs, fastest path query is an important problem and has been well
studied. It focuses on minimizing the total travel time (waiting time+ on-road time) but does …
studied. It focuses on minimizing the total travel time (waiting time+ on-road time) but does …
Group-based recurrent neural networks for POI recommendation
With the development of mobile Internet, many location-based services have accumulated a
large amount of data that can be used for point-of-interest (POI) recommendation. However …
large amount of data that can be used for point-of-interest (POI) recommendation. However …
Route search and planning: A survey
Route search and planning have been playing an important role in spatial data
management and location-based social services. In this light, we conduct a survey on …
management and location-based social services. In this light, we conduct a survey on …