T-Crowd: Effective Crowdsourcing for Tabular Data
2018 IEEE 34th International Conference on Data Engineering (ICDE)(2018)
摘要
We study the effective use of crowdsourcing in filling missing values in a given relation (e.g., a table containing different attributes of celebrity stars, such as nationality and age). A task given to a worker typically consists of questions about the missing attribute values (e.g., what is the age of Jet Li?). Existing work often treats related attributes independently, leading to suboptimal performance. We present T-Crowd: a crowdsourcing system that considers attribute relationships. T-Crowd integrates each worker's answers on different attributes to effectively learn his/her trustworthiness and the true data values. Our solution seamlessly supports categorical and continuous attributes. Our experiments on real datasets show that T-Crowd outperforms state-of-the-art methods, improving the quality of truth inference.
更多查看译文
关键词
Crowdsourcing,Tabular Data
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络