Label distribution similarity-based noise correction for crowdsourcing
Author:
Publisher
Springer Science and Business Media LLC
Subject
General Computer Science,Theoretical Computer Science
Link
https://link.springer.com/content/pdf/10.1007/s11704-023-2751-3.pdf
Reference37 articles.
1. Jiang L, Zhang L, Li C, Wu J. A correlation-based feature weighting filter for naive bayes. IEEE Transactions on Knowledge and Data Engineering, 2019, 31(2): 201–213
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3. Sheng V S, Provost F J, Ipeirotis P G. Get another label? Improving data quality and data mining using multiple, noisy labelers. In: Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. 2008, 614–622
4. Snow R, O’Connor B, Jurafsky D, Ng A Y. Cheap and fast - but is it good?: evaluating non-expert annotations for natural language tasks. In: Proceedings of the Conference on Empirical Methods in Natural Language Processing. 2008, 254–263
5. Zhang J. Knowledge learning with crowdsourcing: a brief review and systematic perspective. IEEE/CAA Journal of Automatica Sinica, 2022, 9(5): 749–762
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