A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2015; you can also visit the original URL.
The file type is
Given a set of records, an ER algorithm finds records that refer to the same real-world entity. Humans can often determine if two records refer to the same entity, and hence we study the problem of selecting questions to ask errorprone humans. We give a Maximum Likelihood formulation for the problem of finding the "most beneficial" questions to ask next. Our theoretical results lead to a lightweight and practical algorithm, bDENSE, for selecting questions to ask humans. Our experimental resultsdoi:10.1109/icde.2015.7113286 dblp:conf/icde/VerroiosG15 fatcat:og5jjpyuubahpejw434z7tjosi