Generating Explanations to Understand and Repair Embedding-based Entity Alignment

arXiv:2312.04877v3 Announce Type: replace
Abstract: Entity alignment (EA) seeks identical entities in different knowledge graphs, which is a long-standing task in the database research. Recent work leverages deep learning to embed entities in vector space and align them via nearest neighbor search. Although embedding-based EA has gained marked success in recent years, it lacks explanations for alignment decisions. In this paper, we present the first framework that can generate explanations for understanding and repairing embedding-based EA results. Given an EA …

abstract alignment arxiv cs.cl cs.db database deep learning embed embedding graphs knowledge knowledge graphs research search space success them type vector via work