Large-scale Entity Alignment via Knowledge Graph Merging, Partitioning and Embedding. (arXiv:2208.11125v1 [cs.LG])

Entity alignment is a crucial task in knowledge graph fusion. However, most
entity alignment approaches have the scalability problem. Recent methods
address this issue by dividing large KGs into small blocks for embedding and
alignment learning in each. However, such a partitioning and learning process
results in an excessive loss of structure and alignment. Therefore, in this
work, we propose a scalable GNN-based entity alignment approach to reduce the
structure and alignment loss from three perspectives. First, we propose a …

alignment arxiv embedding graph knowledge knowledge graph lg merging partitioning scale