In this paper, we study the Time-Dependent k Nearest Neighbor (TD-k NN) query on moving
objects that aims to return k objects arriving at the query location with the least traveling cost …

Computing the shortest path for any two given vertices is an important problem in road
networks. Since real road networks are dynamically updated due to real-time traffic …

Computing top-k nearest neighbors (kNN) is a fundamental problem in road networks.
Existing solutions either need a complicated parameter configuration in index construction …

Finding the fastest path in the time-dependent road network is time consuming because its
problem complexity is, where is the size of the result's time-dependent function, and are the …

Shortest path computation is a fundamental operation in many application domains and is
especially challenging in frequently evolving small-world networks (ie, graphs in which …

Dynamic Graph Neural Networks (DGNNs) have demonstrated exceptional performance at
dynamic-graph analysis tasks. However, the costs exceed those incurred by other learning …

Public transportation plays a vital role in mitigating traffic congestion and reducing carbon
emissions. The Top-k Nearest Neighbor (k NN) search in public transportation networks is a …

Top-k Nearest Neighbors (kNN) problem on road network has numerous applications on
location-based services. As direct search using the Dijkstra's algorithm results in a large …

The nearest neighbors query problem on road networks constitutes a crucial aspect of
location-oriented services and has useful practical implications; eg, it can locate the k …

The challenge of optimally placing facilities to maximize coverage within road networks is a
critical problem with significant implications for urban planning, emergency response, and …