Hierarchical Crowdsourcing for Data Labeling with Heterogeneous Crowd-Reference-Cited by-同舟云学术

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Hierarchical Crowdsourcing for Data Labeling with Heterogeneous Crowd

Published:2023-04 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE 39th International Conference on Data Engineering (ICDE)
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Author:

Zhang Haodi¹,Huang Wenxi¹,Su Zhenhan¹,Chen Junyang¹,Jiang Di²,Fan Lixin³,Zhang Chen⁴,Lian Defu⁵,Wu Kaishun¹

Affiliation:

1. Shenzhen University,College of Computer Science and Software Engineering

2. Shenzhen University,WeBank Institute of Financial Technology

3. Webank Co., Ltd.

4. Hong Kong Polytechnic University,Department of Computing

5. University of Science and Technology of China,School of Data Science

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10184508/10184509/10184732.pdf?arnumber=10184732

Reference39 articles.

1. A game-based framework for crowdsourced data labeling

2. Bayesian classifier combination;kim;Proceedings of Artificial Intelligence and Statistics (AISTATS),2012

3. Simple Multiple Noisy Label Utilization Strategies

4. Truth Inference at Scale: A Bayesian Model for Adjudicating Highly Redundant Crowd Annotations

5. Majority Voting and Pairing with Multiple Noisy Labeling

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