Next location prediction has recently gained great attention from researchers due to its
importance in different application areas. Recent growth of location-based service …

Numerous advancements in various fields, including pattern recognition and image
classification, have been made thanks to modern computer vision and machine learning …

Road network is the core component of urban transportation, and it is widely useful in
various traffic-related systems and applications. Due to its important role, it is essential to …

Modeling trajectory data is a building block for many smart-mobility initiatives. Existing
approaches apply shallow models such as Markov chain and inverse reinforcement learning …

Personalized Route Recommendation (PRR) aims to generate user-specific route
suggestions in response to users' route queries. Early studies cast the PRR task as a …

Graph machine learning methods excel at leveraging pairwise relations present in the data.
However, graphs are unable to fully capture the multi-way interactions inherent in many …

Travel time estimation of a given route with respect to real-time traffic condition is extremely
useful for many applications like route planning. We argue that it is even more useful to …

With the development of location-acquisition technologies, there are a huge number of
mobile trajectories generated and accumulated in a variety of domains. However, due to the …

The aim of this work is to introduce simplicial attention networks (SANs), ie, novel neural
architectures that operate on data defined on simplicial complexes leveraging masked self …

With the advances of web-of-things, human mobility, eg, GPS trajectories of vehicles,
sharing bikes, and mobile devices, reflects people's travel patterns and preferences, which …