Domain Weighted Majority Voting for Crowdsourcing
文献类型：期刊论文
| 作者 | Dapeng Tao; Jun Cheng; Zhengtao Yu; Kun Yue; Lizhen Wang |
| 刊名 | IEEE Transactions on Neural Networks and Learning Systems
 |
| 出版日期 | 2018 |
| 文献子类 | 期刊论文 |
| 英文摘要 | Crowdsourcing labeling systems provide an efficient way to generate multiple inaccurate labels for given observations. If the competence level or the ``reputation,'' which can be explained as the probabilities of annotating the right label, for each crowdsourcing annotators is equal and biased to annotate the right label, majority voting (MV) is the optimal decision rule for merging the multiple labels into a single reliable one. However, in practice, the competence levels of annotators employed by the crowdsourcing labeling systems are often diverse very much. In these cases, weighted MV is more preferred. The weights should be determined by the competence levels. However, since the annotators are anonymous and the ground-truth labels are usually unknown, it is hard to compute the competence levels of the annotators directly. In this paper, we propose to learn the weights for weighted MV by exploiting the expertise of annotators. Specifically, we model the domain knowledge of different annotators with different distributions and treat the crowdsourcing problem as a domain adaptation problem. The annotators provide labels to the source domains and the target domain is assumed to be associated with the ground-truth labels. The weights are obtained by matching the source domains with the target domain. Although the target-domain labels are unknown, we prove that they could be estimated under mild conditions. Both theoretical and empirical analyses verify the effectiveness of the proposed method. Large performance gains are shown for specific data sets. |
| URL标识 | 查看原文 |
| 语种 | 英语 |
| 源URL | [http://ir.siat.ac.cn:8080/handle/172644/13571]  |
| 专题 | 深圳先进技术研究院_集成所 |
| 推荐引用方式 GB/T 7714 | Dapeng Tao,Jun Cheng,Zhengtao Yu,et al. Domain Weighted Majority Voting for Crowdsourcing[J]. IEEE Transactions on Neural Networks and Learning Systems,2018. |
| APA | Dapeng Tao,Jun Cheng,Zhengtao Yu,Kun Yue,& Lizhen Wang.(2018).Domain Weighted Majority Voting for Crowdsourcing.IEEE Transactions on Neural Networks and Learning Systems. |
| MLA | Dapeng Tao,et al."Domain Weighted Majority Voting for Crowdsourcing".IEEE Transactions on Neural Networks and Learning Systems (2018). |
入库方式： OAI收割
来源：深圳先进技术研究院
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。