Unsupervised embedding of trajectories captures the latent structure of mobility

dataset

posted on 2020-10-19, 15:06 authored by Dakota MurrayDakota Murray, Jisung Yoon, Sadamori Kojaku, Rodrigo CostasRodrigo Costas, Woo-sung Jung, Staša Milojević, Yong-Yeol ahn

Data related to the paper titled "Unsupervised embedding of trajectories captures the latent structure of mobility", including trained neural embeddings and metadata necessary to reproduce reproduce results.

Due to their proprietary nature, raw data cannot be made available.

Information regarding the files contained in these folders, as well as instructions for producing the figures relating to this study, can be found at the following GitHub repository:

https://github.com/murrayds/sci-mobility-emb/Data

Funding

FA9550-19-1-0391

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Keywords

human mobility Scientometrics Neural Embeddings Human Geography not elsewhere classified Migration Science Policy Artificial Intelligence and Image Processing

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CC BY 4.0

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