Traditional statistical data on international migration suffers from the problems (gaps) of inconsistency in definitions, differences in geographical coverages, absence of...

Non-Pharmaceutical Interventions (NPIs), aimed at reducing the diffusion of the COVID-19 pandemic, have dramatically influenced our everyday behaviour. In this experiment, we...

We conduct extensive experiments on public datasets of bike and taxi rides to show that MoGAN outperforms the classical Gravity and Radiation models regarding the realism of...

The increasingly crucial role of human displacements in complex societal phenomena, such as traffic congestion, segregation, and the diffusion of epidemics, is attracting the...

We conducted experiments on mobility flows in England, Italy, and New York State to show that Deep Gravity achieves a significant increase in performance, especially in...

Deep Gravity is an effective model to generate flow probabilities that exploits many features (e.g., land use, road network, transport, food, health facilities) extracted from...

Mining with big data or big data mining has become an active research area. Running current analytical methodologies and software tools on a single personal computer cannot...

This tutorial provides an 'Introduction to Learning to Rank' and focuses on 'Dealing with the Efficiency/Effectiveness trade-off in Web Search'. Moreover, it provides two...

The non-pharmaceutical interventions (NPIs), aimed at reducing the diffusion of the COVID-19 pandemic, has dramatically influenced our behaviour in everyday life. We developed...

We used the mobility-emission methods (https://data.d4science.org/ctlg/ResourceCatalogue/mobility-emissions) to perform experiments on real GPS trajectories describing 433,272...

We created a dataset that comprises the mobile phone activity of sixty-five participants for whom the geographical coordinates of their residence location are known. The...

Inferring mobile phone users' home location, i.e., assigning a location in space to a user based on data generated by the mobile phone network, is a central task in leveraging...

Modelling human mobility is crucial in several scientific areas, from urban planning to epidemic modeling, traffic forecasting, and what-if analysis. Existing models focus on...

GeoSim, proposed by Toole et al. [1], is a mechanistic generative model for human mobility. GeoSim takes into account the social dimension between individuals during the...

In this experiment we simulate the mobility of individuals in New York City, London, and Tokyo, using STS-EPR. For each city, we compare the synthetic trajectories generated...

This dataset contains the geometry of about 20.000 census sectors and limited demographic information of Tuscany region (Italy).

How did the COVID-19 epidemics change our mobility habits, and how did it impact on people’s well-being and on the virus transmissibility? In the first webinar of the seminar...

This resource consists of a visual analytics framework and a set of supporting tools for deriving place meaning and reconstructing personal mobility diaries from episodic...

It is a general method to determine the influence of social and mobility behavior over a specific geographical area in order to evaluate to what extent the current...

Carpooling, i.e., the act where two or more travelers share the same car for a common trip, is one of the possibilities brought forward to reduce traffic and its...