CrowdRecruiter
Author:
Affiliation:
1. Institut Mines-Télécom, Evry, France
2. University of Massachusetts Lowell, MA
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/2632048.2632059
Reference45 articles.
1. Mobile crowdsensing: current state and future challenges
2. An energy-efficient quality adaptive framework for multi-modal sensor context recognition
3. Supporting Energy-Efficient Uploading Strategies for Continuous Sensing Applications on Mobile Phones
4. Piggyback CrowdSensing (PCS)
Cited by 210 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. LSTM-Oppurs: Opportunistic user recruitment strategy based on deep learning in mobile crowdsensing system;Future Generation Computer Systems;2025-01
2. Collaborative Route Planning of UAVs, Workers, and Cars for Crowdsensing in Disaster Response;IEEE/ACM Transactions on Networking;2024-08
3. Crowdsourcing incentive mechanisms for cross-platform tasks: A weighted average maximization approach;Engineering Applications of Artificial Intelligence;2024-07
4. Socially-aware and privacy-preserving multi-objective worker recruitment in mobile crowd sensing;Peer-to-Peer Networking and Applications;2024-02-08
5. Tag-based self-learning task recommendation for mobile crowdsensing via collaborative multi-expert system;Computer Communications;2024-01
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