Generative Models for Synthetic Urban Mobility Data: A Systematic Literature Review

Fuente: arXiv
Salvato in:
Dettagli Bibliografici
Autori principali: Kapp, Alexandra, Hansmeyer, Julia, Mihaljević, Helena
Natura: Preprint
Pubblicazione: 2024
Soggetti:
Accesso online:
Tags: Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
_version_ 1866917720840208384
author Kapp, Alexandra
Hansmeyer, Julia
Mihaljević, Helena
author_facet Kapp, Alexandra
Hansmeyer, Julia
Mihaljević, Helena
contents Although highly valuable for a variety of applications, urban mobility data is rarely made openly available as it contains sensitive personal information. Synthetic data aims to solve this issue by generating artificial data that resembles an original dataset in structural and statistical characteristics, but omits sensitive information. For mobility data, a large number of corresponding models have been proposed in the last decade. This systematic review provides a structured comparative overview of the current state of this heterogeneous, active field of research. A special focus is put on the applicability of the reviewed models in practice.
format Preprint
id arxiv_https___arxiv_org_abs_2407_09198
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Generative Models for Synthetic Urban Mobility Data: A Systematic Literature Review
Kapp, Alexandra
Hansmeyer, Julia
Mihaljević, Helena
Cryptography and Security
Although highly valuable for a variety of applications, urban mobility data is rarely made openly available as it contains sensitive personal information. Synthetic data aims to solve this issue by generating artificial data that resembles an original dataset in structural and statistical characteristics, but omits sensitive information. For mobility data, a large number of corresponding models have been proposed in the last decade. This systematic review provides a structured comparative overview of the current state of this heterogeneous, active field of research. A special focus is put on the applicability of the reviewed models in practice.
title Generative Models for Synthetic Urban Mobility Data: A Systematic Literature Review
topic Cryptography and Security
url https://arxiv.org/abs/2407.09198