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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...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2022
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| 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 |