Corpus ID: 207847375

Active Multi-Label Crowd Consensus

@article{Tu2019ActiveMC,
  title={Active Multi-Label Crowd Consensus},
  author={Jinzheng Tu and Guoxian Yu and C. Domeniconi and J. Wang and X. Zhang},
  journal={ArXiv},
  year={2019},
  volume={abs/1911.02789}
}
Crowdsourcing is an economic and efficient strategy aimed at collecting annotations of data through an online platform. Crowd workers with different expertise are paid for their service, and the task requester usually has a limited budget. How to collect reliable annotations for multi-label data and how to compute the consensus within budget is an interesting and challenging, but rarely studied, problem. In this paper, we propose a novel approach to accomplish Active Multi-label Crowd Consensus… Expand
1 Citations
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