FedLens: federated learning-based privacy-preserving mobile crowdsensing for virtual tourism-Reference-Cited by-同舟云学术

FedLens: federated learning-based privacy-preserving mobile crowdsensing for virtual tourism

Published:2022-01-12 Issue: Volume: Page:
ISSN:1614-5046
Container-title:Innovations in Systems and Software Engineering
language:en
Short-container-title:Innovations Syst Softw Eng

Author:

De Debashis^ORCID

Publisher

Springer Science and Business Media LLC

Subject

Software

Link

https://link.springer.com/content/pdf/10.1007/s11334-021-00430-6.pdf

Reference30 articles.

1. Basak B, Debashis D (2021) GeoLens: geospatial location exploration using mobile crowdsensing in tourism 4.0: a case study of Kunjanagar Eco Park, Falakata, West Bengal. In: AISC, Springer, 2021 International conference on advanced computing and applications, India

2. Carbone F (2020) Tourism destination management post COVID-19 pandemic: a new humanism for a human-centred tourism (tourism 5.0). Turismo Mundial Crise Sanitária e Futuro 43:56

3. Kbaier ME, Ben H, Hela M, Saoussen K (2017) A personalized hybrid tourism recommender system. In: 2017 IEEE/ACS 14th international conference on computer systems and applications (AICCSA), pp 244–250. IEEE

4. Bhattacharya A, Debashis D (2021) SigSense: mobile crowdsensing based incentive aware geospatial signal monitoring for base station installation recommendation using mixed reality game. Wirel Personal Commun 7:1–32

5. Zhang X, Rongxing L, Jun S, Fengwei W, Hui Z, Ali AG (2021) FedSky: an efficient and privacy-preserving scheme for federated mobile crowdsensing. IEEE IOT J 3:10987

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