An optimization approach for worker selection in crowdsourcing systems

Author:

Shen Songhao,Ji MiaomiaoORCID,Wu ZhibinORCID,Yang Xieyu

Funder

Fundamental Research Funds for the Central Universities

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

General Engineering,General Computer Science

Reference46 articles.

1. A framework for optimal worker selection in spatial crowdsourcing using Bayesian network;Abdullah;IEEE Access,2020

2. Multi-worker multi-task selection framework in mobile crowd sourcing;Abououf;Journal of Network and Computer Applications,2019

3. Picking peaches or squeezing lemons: Selecting crowdsourcing workers for reducing cost of redundancy;Adamska;Computational Science ICCS,2020

4. The wisdom of amateur crowds: evidence from an online community of sports tipsters;Alasdair;European Journal of Operational Research,2018

5. Quality control in crowdsourcing systems: Issues and directions;Allahbakhsh;IEEE Internet Computing,2013

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2. Reputation aware optimal team formation for collaborative software crowdsourcing in industry 5.0;Journal of King Saud University - Computer and Information Sciences;2023-09

3. Quality Evaluation of Multimedia Service in Crowdsourcing Platform based on Evolutionary Game Theory;2023 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB);2023-06-14

4. A Blockchain-Based Crowdsourcing Loan Platform for Funding Higher Education in Developing Countries;IEEE Access;2023

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