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FedGeoTour: Federated learning-based geostatistical approach to privacy-preserving mobile crowdsensing for sustainable tourism

Tapasi Bhattacharjee et al.

Information Technology & Tourism2026https://doi.org/10.1007/s40558-026-00364-4article
AJG 1ABDC A
Weight
0.50

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https://doi.org/https://doi.org/10.1007/s40558-026-00364-4

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@article{tapasi2026,
  title        = {{FedGeoTour: Federated learning-based geostatistical approach to privacy-preserving mobile crowdsensing for sustainable tourism}},
  author       = {Tapasi Bhattacharjee et al.},
  journal      = {Information Technology & Tourism},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1007/s40558-026-00364-4},
}

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FedGeoTour: Federated learning-based geostatistical approach to privacy-preserving mobile crowdsensing for sustainable tourism

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.