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Learning representations for quality estimation of crowdsourced submissions

文献类型：期刊论文

作者Shen, Huawei2; Lyu, Shanshan1,2; Ouyang, Wentao2; Cheng, Xueqi2
刊名INFORMATION PROCESSING & MANAGEMENT
出版日期2019-07-01
卷号56期号:4页码:1484-1493
关键词Crowdsourcing Quality estimation Embedding
ISSN号0306-4573
DOI10.1016/j.ipm.2018.10.020
英文摘要The problem of quality estimation of crowdsourced work is of great importance. Although a variety of aggregation methods have been proposed to find high-quality structured claims in multiple-choice crowdsourcing tasks such as item labeling, they do not apply to more general tasks, such as article writing and brand design with unstructured submissions. One possibility to tackle this problem is to ask another set of crowd workers to review and grade each submission, essentially transforming unstructured submissions into structured ratings. Nevertheless, such an approach incurs unnecessary monetary cost and delay. In this paper, we address this problem by exploiting task requesters' historical feedback and directly modeling the submission quality. We propose two embedding-based methods where the first one learns worker embedding and the second one learns both worker embedding and meta information embedding, with additional consideration of neighborhood similarity. Experimental results on three large-scale crowdsourcing data sets demonstrate that our embedding-based feature-learning methods perform much better than feature-engineering methods that use popular learning-to-rank algorithms. At the same time, our methods do not require additional crowdsourced grading.
资助项目National Key Research and Development Program of China[2017YFB0803302] ; National Basic Research Program of China (973Program)[2014CB340401] ; National Natural Science Foundation of China[61602439] ; National Natural Science Foundation of China[61472400] ; National Natural Science Foundation of China[91746301] ; CAS Pioneer Hundred Talents Program[2920164120]
WOS研究方向Computer Science ; Information Science & Library Science
语种英语
WOS记录号WOS:000469907200020
出版者ELSEVIER SCI LTD
源URL[http://119.78.100.204/handle/2XEOYT63/4207]  
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Lyu, Shanshan
作者单位1.Univ Chinese Acad Sci, Beijing, Peoples R China
2.Chinese Acad Sci, Inst Comp Technol, CAS Key Lab Network Data Sci & Technol, Beijing, Peoples R China
推荐引用方式
GB/T 7714		 Shen, Huawei,Lyu, Shanshan,Ouyang, Wentao,et al. Learning representations for quality estimation of crowdsourced submissions[J]. INFORMATION PROCESSING & MANAGEMENT,2019,56(4):1484-1493.
APA Shen, Huawei,Lyu, Shanshan,Ouyang, Wentao,&Cheng, Xueqi.(2019).Learning representations for quality estimation of crowdsourced submissions.INFORMATION PROCESSING & MANAGEMENT,56(4),1484-1493.
MLA Shen, Huawei,et al."Learning representations for quality estimation of crowdsourced submissions".INFORMATION PROCESSING & MANAGEMENT 56.4(2019):1484-1493.

入库方式： OAI收割

来源：计算技术研究所

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