Graph embedding is an important technique for improving the quality of link prediction
models on knowledge graphs. Although embedding based on neural networks can capture …

Over the past decade, transportation network companies (TNCs) have disrupted the urban
transportation landscape. These services are replacing many traditional vehicle for hire …

Purpose To solve the problem, a mathematical model is proposed; it relies on a directed
acyclic graph (DAG), in which arcs are used to indicate whether a pair of appointments can …

Ridesharing services linked to mobile devices are increasingly playing a major role in
human mobility in urban areas. With the recent release of Uber Movement data for certain …

Estimating temporal patterns in travel times along road segments in urban settings is of
central importance to traffic engineers and city planners. In this work, we propose a …

Background. TranSEC emerged as a logical outgrowth from the VTO/EEMS funded Big Data
Systems for Mobility (BDSM) project. BDSM's objective was to develop the data science and …

Big data and high performance computing paradigms are poised to revolutionize the
transportation sector in the coming years [32]. A key requirement for a city transportation …