Semi-constraint Optimal Transport for Entity Alignment with Dangling Cases. (arXiv:2203.05744v3 [cs.CL] UPDATED)

Entity alignment (EA) merges knowledge graphs (KGs) by identifying the
equivalent entities in different graphs, which can effectively enrich knowledge
representations of KGs. However, in practice, different KGs often include
dangling entities whose counterparts cannot be found in the other graph, which
limits the performance of EA methods. To improve EA with dangling entities, we
propose an unsupervised method called Semi-constraint Optimal Transport for
Entity Alignment in Dangling cases (SoTead). Our main idea is to model the
entity alignment between …

alignment arxiv cases transport