Human mobility from theory to practice: Data, models and applications

Filippo Simini, Roberto Pellungrini, Gianni Barlacchi, Luca Pappalardo

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

2 Citations (Scopus)
479 Downloads (Pure)

Abstract

The inclusion of tracking technologies in personal devices opened the doors to the analysis of large sets of mobility data like GPS traces and call detail records. This tutorial presents an overview of both modeling principles of human mobility and machine learning models applicable to specific problems. We review the state of the art of five main aspects in human mobility: (1) human mobility data landscape; (2) key measures of individual and collective mobility; (3) generative models at the level of individual, population and mixture of the two; (4) next location prediction algorithms; (5) applications for social good. For each aspect, we show experiments and simulations using the Python library "scikit-mobility" developed by the presenters of the tutorial.

Original languageEnglish
Title of host publicationThe Web Conference 2019 - Companion of the World Wide Web Conference, WWW 2019
Subtitle of host publicationSan Francisco, USA — May 13 - 17, 2019
PublisherAssociation for Computing Machinery (ACM)
Pages1311-1312
Number of pages2
ISBN (Electronic)9781450366755
DOIs
Publication statusPublished - 13 May 2019
Event2019 World Wide Web Conference, WWW 2019 - San Francisco, United States
Duration: 13 May 201917 May 2019

Conference

Conference2019 World Wide Web Conference, WWW 2019
CountryUnited States
CitySan Francisco
Period13/05/1917/05/19

Keywords

  • Artificial Intelligence
  • Data Science
  • Generative Models
  • Human Mobility
  • Predictive Algorithms

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