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...

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...

This experiment performs a simulation (using SUMO) of the urban impact of two navigation services (TomTom and OpenRoutingService) in the city of Milan, Italy.

Synthetic shopping retail consumption data generated with TVAE. The dataset provides monthly information on the spending of synthetic customers belonging to two classes (i.e.,...

This dataset comprises tabular information related to the movement of taxis in the city of Porto, Portugal. For every taxi journey, we segmented the trajectory into 20...

A synthetically generated dataset representing purpose-of-motion data in the format of individual mobility networks.

This is a two-stage predictive model for the mobility of scientists. First, data mining is used to predict which researcher will move in the next year on the basis of their...

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

The dataset comprises pickup and drop-off times and locations of vehicles in 10 European cities for one of the major free-floating car sharing operator. For nine of these...

MyWay is a prediction system which exploits the individual systematic behaviors modeled by mobility profiles to predict human movements. MyWay provides three strategies: the...

Ditras (DIary-based TRAjectory Simulator) is a framework to simulate the spatio-temporal patterns of human mobility. It operates in two steps: the generation of a mobility...

Wearable physiological monitors have become increasingly popular, often worn during people’s daily life, collecting data 24 hours a day, 7 days a week. In the last decade,...

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...

Mass participation sporting events (MPSEs) are viewed as encouraging regular exercise in the population, but concerns have been expressed about the extent to which they are...

This method describes an analytical framework to nowcast well-being by using mobility measures extracted from mobile phone data.

GeoTopics is a system to explore geographical patterns of urban activity. The system collects publicly shared check-ins generated by Foursquare users, that reveal who spends...

We propose a segregation model incorporating mobility constraints to make agents select their location based on distance and location relevance. This study fills this gap by...