Data-driven Techniques for Improving Data Collection
作者:Kuang Chen 作者单位:University of California, Berkeley 加工时间:2013-10-22 信息来源:EECS 索取原文[102 页]
关键词:数据采集;数据驱动;认知模型 摘 要:The main contributions of this dissertation are (1) a probabilistic foundation for data collection, which effectively guides form design, form filling, and value verification; (2)dynamic data entry interface adaptations, which significantly improve data entry accuracy and efficiency; and (3) the design and large-scale evaluation of a hosted-service architecture for data entry.