Worker Selection Towards Data Completion for Online Sparse Crowdsensing

Author:

Liu Wenbin1,Wang En1,Yang Yongjian1,Wu Jie2

Affiliation:

1. Jilin University,College of Computer Science and Technology,China

2. Temple University,Department of Computer and Information Sciences,Philadelphia,USA

Funder

National Natural Science Foundation of China

China Postdoctoral Science Foundation

Baidu

Publisher

IEEE

Reference37 articles.

Cited by 10 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. MACRO: Incentivizing Multi-Leader Game-Based Pareto-Efficient Crowdsourcing for Video Analytics;2024 IEEE 40th International Conference on Data Engineering (ICDE);2024-05-13

2. Maximizing the Total Utility of Requesters in Crowdsourcing;2024 10th IEEE International Conference on High Performance and Smart Computing (HPSC);2024-05-10

3. Self-Interested Coalitional Crowdsensing for Multi-Agent Interactive Environment Monitoring;Sensors;2024-01-14

4. Robust Data Inference and Cost-Effective Cell Selection for Sparse Mobile Crowdsensing;IEEE/ACM Transactions on Networking;2024

5. Enhancing Sparse Mobile CrowdSensing With Manifold Optimization and Differential Privacy;IEEE Transactions on Information Forensics and Security;2024

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