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Graph-based representation for identifying individual travel activities with spatiotemporal trajectories and POI data

Individual daily travel activities (e.g., work, eating) are identified with various machine learning models (e.g., Bayesian Network, Random Forest) for understanding people’s frequent travel purposes. However, labor-intensive engineering work is often required to extract effective features. Addition...

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Detalles Bibliográficos
Autores principales: Liu, Xinyi, Wu, Meiliu, Peng, Bo, Huang, Qunying
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9492902/
https://www.ncbi.nlm.nih.gov/pubmed/36130956
http://dx.doi.org/10.1038/s41598-022-19441-9