Inconsistency-driven approach for human-in-the-loop entity matching - Hiroyoshi Ito; Takahiro Koizumi; Ryuji Yoshimoto; Yukihiro Fukushima; Takashi Harada; Atsuyuki Morishima (Information Research: An International Electronic Journal)
Introduction. Entity matching is a fundamental operation in a wide range of information management applications and a tremendous number of methods have been proposed to address the problem. Human-in-the-loop entity matching is a human-AI collaborative approach which is effective when the data for entity matching is incomplete or requires domain knowledge. A typical human-in-the-loop approach is to allow a machine-learning-based matcher to ask humans to match entities when it cannot match them with high confidence. However, ML-based matchers cannot avoid the unknown-unknown problem, i.e., they can resolve the entities incorrectly with high confidence.