The importance of manual assessment in link discovery

Darren Wei Che Huang, Andrew Trotman, Shlomo Geva

Abstract: Using a ground truth extracted from the Wikipedia, and a ground truth created through manual assessment, we show that the apparent performance advantage seen in machine learning approaches to link discovery are an artifact of trivial links that are actively rejected by manual assessors.