CrowdCleaner: A Data Cleaning System Based on Crowdsourcing

Chen Ye, Hongzhi Wang, Keli Li, Qian Chen, Jianhua Chen, Jiangduo Song, Weidong Yuan

Abstract: As data in real life is often dirty, data cleaning is a natural way to improve the data quality. However, due to the lack of human knowledge, existing automatic data cleaning systems cannot find the proper values for dirty data. Thus we propose an online data cleaning system CrowdCleaner based on Crowdsourcing. CrowdCleaner provides a friendly interface for users dealing with different data quality problems. In this demonstration, we show the architecture of CrowdCleaner and highlight a few of its key features. We will show the process of the CrowdCleaner to clean data.