Deep learning has recently become very popular on account of its incredible success in
many complex datadriven applications, including image classification and speech …

Abstract Intelligent Transportation Systems (ITS) is not a new concept. Notably, ITS has been
cited in various journal articles and proceedings papers around the world, and it has …

Graph representation learning for static graphs is a well studied topic. Recently, a few
studies have focused on learning temporal information in addition to the topology of a graph …

Mobile user profiles are a summary of characteristics of user-specific mobile activities.
Mobile user profiling is to extract a user's interest and behavioral patterns from mobile …

Unsupervised spatial representation learning aims to automatically identify effective features
of geographic entities (ie, regions) from unlabeled yet structural geographical data. Existing …

Multi-modal transportation recommendation aims to provide the most appropriate travel
route with various transportation modes according to certain criteria. After analyzing large …

Multi-modal transportation recommendation has a goal of recommending a travel plan which
considers various transportation modes, such as walking, cycling, automobile, and public …

Driver profiling, which is the process of extracting driver preferences and behavioral patterns
from collected driving data, can be performed on a microscopic or macroscopic scale …

Increasing urbanization across the globe has coincided with greater access to urban data;
this enables researchers and city administrators with better tools to understand urban …

Personalization in driving behavior research is crucial for developing intelligent vehicles that
can safely coexist with human-driven vehicles in mixed-traffic environments. By accounting …