Machine learning and ontology in eCoaching for personalized activity level monitoring and recommendation generation
- DOI
- 10.1038/s41598-022-24118-4
- Published
- 2022-11-18
- Container
- Scientific Reports
- Publisher
- Springer Science and Business Media LLC
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1038/s41598-022-24118-4,
title = {Machine learning and ontology in eCoaching for personalized activity level monitoring and recommendation generation},
author = {Ayan Chatterjee and Nibedita Pahari and Andreas Prinz and Michael Riegler},
year = {2022},
journal = {Scientific Reports},
doi = {10.1038/s41598-022-24118-4},
url = {https://doi.org/10.1038/s41598-022-24118-4}
}RIS
TY - JOUR TI - Machine learning and ontology in eCoaching for personalized activity level monitoring and recommendation generation AU - Ayan Chatterjee AU - Nibedita Pahari AU - Andreas Prinz AU - Michael Riegler PY - 2022 JO - Scientific Reports DO - 10.1038/s41598-022-24118-4 UR - https://doi.org/10.1038/s41598-022-24118-4 ER -
APA
Chatterjee, A., Pahari, N., Prinz, A., & Riegler, M. (2022). Machine learning and ontology in eCoaching for personalized activity level monitoring and recommendation generation. Scientific Reports. https://doi.org/10.1038/s41598-022-24118-4
Source records
- crossref · retrieved 2026-11-10T14:42:07.985Z