Learning from biased crowdsourced labeling with deep clustering
作者：
Highlights：
• The phenomenon of biased labeling usually existing in the scenario of crowdsourcing.
• Biased labeling is a critical factor that effects label aggregation performance.
• Deep clustering estimates the underlying label distribution and detect the bias.
摘要
•The phenomenon of biased labeling usually existing in the scenario of crowdsourcing.•Biased labeling is a critical factor that effects label aggregation performance.•Deep clustering estimates the underlying label distribution and detect the bias.
论文关键词：Crowdsourcing,Label aggregation,Classification,Biased labeling,Clustering
论文评审过程：Received 25 March 2022, Revised 27 June 2022, Accepted 15 August 2022, Available online 23 August 2022, Version of Record 5 September 2022.
论文官网地址：https://doi.org/10.1016/j.eswa.2022.118608
