A Framework for Optimal Worker Selection in Spatial Crowdsourcing Using Bayesian Network-Reference-Cited by-同舟云学术

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A Framework for Optimal Worker Selection in Spatial Crowdsourcing Using Bayesian Network

Published:2020 Issue: Volume:8 Page:120218-120233
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Abdullah Nor Aniza^ORCID,Rahman Mohammad Mustaneer^ORCID,Rahman Md. Mujibur^ORCID,Ghauth Khairil Imran

Funder

University of Malaya Research Grant

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science

Link

http://xplorestaging.ieee.org/ielx7/6287639/8948470/09127467.pdf?arnumber=9127467

Cited by 9 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. Multilabel classification using crowdsourcing under budget constraints;Knowledge and Information Systems;2023-09-09

2. A Framework of Quality-Aware Personalized Task Matching For Mobile Crowdsensing;2023 IEEE 13th Symposium on Computer Applications & Industrial Electronics (ISCAIE);2023-05-20

3. Distributed spatial crowdsourcing based task allocation in Ocean Internet of Things;Earth Science Informatics;2023-02-14

4. A Trustworthiness-Aware Spatial Task Allocation using a Fuzzy-based Trust and Reputation System Approach;Expert Systems with Applications;2023-01

5. An optimization approach for worker selection in crowdsourcing systems;Computers & Industrial Engineering;2022-11

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