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- research-articleJune 2023
A Semi-supervised Sensing Rate Learning based CMAB scheme to combat COVID-19 by trustful data collection in the crowd
- Jianheng Tang,
- Kejia Fan,
- Wenxuan Xie,
- Luomin Zeng,
- Feijiang Han,
- Guosheng Huang,
- Tian Wang,
- Anfeng Liu,
- Shaobo Zhang
Computer Communications (COMS), Volume 206, Issue CPages 85–100https://doi.org/10.1016/j.comcom.2023.04.030AbstractThe recruitment of trustworthy and high-quality workers is an important research issue for MCS. Previous studies either assume that the qualities of workers are known in advance, or assume that the platform knows the qualities of workers once it ...
Highlights- Model the UWR problem as a multi-armed bandit reverse auction problem, and design an UCB-based algorithm to separate the exploration and exploitation.
- A Semi-supervised Sensing Rate Learning approach is proposed to quickly and ...
- research-articleNovember 2022
Area coverage-based worker recruitment under geo-indistinguishability
Computer Networks: The International Journal of Computer and Telecommunications Networking (CNTW), Volume 217, Issue Chttps://doi.org/10.1016/j.comnet.2022.109340AbstractLocation information is usually required for area coverage-based worker recruitment in mobile crowdsensing, which may pose considerable threats to individual privacy without proper privacy protection. In this paper, we investigate the problem of ...
- ArticleDecember 2021
Worker Recruitment Based on Edge-Cloud Collaboration in Mobile Crowdsensing System
Algorithms and Architectures for Parallel ProcessingPages 406–420https://doi.org/10.1007/978-3-030-95388-1_27AbstractIn recent years, with the rapid development of mobile Internet and smart sensor technology, mobile crowdsensing (MCS) computing model has attracted wide concern in academia, industry and business circles. MCS utilizes the sensing and computing ...
- research-articleMarch 2019
Multi-worker multi-task selection framework in mobile crowd sourcing
Journal of Network and Computer Applications (JNCA), Volume 130, Issue CPages 52–62https://doi.org/10.1016/j.jnca.2019.01.008AbstractIn this paper, we address the problem of multi-worker multi-task allocation for mobile crowd sourcing systems (MCS), known to be hard to solve. The existing solutions for multi-task selection are mainly sequential assignments and/or ...
- research-articleDecember 2018
Passerby Crowdsourcing: Workers' Behavior and Data Quality Management
- Eiichi Iwamoto,
- Masaki Matsubara,
- Chihiro Ota,
- Satoshi Nakamura,
- Tsutomu Terada,
- Hiroyuki Kitagawa,
- Atsuyuki Morishima
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT), Volume 2, Issue 4Article No.: 169, Pages 1–20https://doi.org/10.1145/3287047Worker recruitment is one of the important problems in crowdsourcing, and many proposals have been presented for placing equipment in physical spaces for recruiting workers. One of the essential challenges of the approach is how to keep people attracted ...