Dangling-Aware Entity Alignment with Mixed High-Order Proximities. (arXiv:2205.02406v1 [cs.CL])

Web: http://arxiv.org/abs/2205.02406

We study dangling-aware entity alignment in knowledge graphs (KGs), which is
an underexplored but important problem. As different KGs are naturally
constructed by different sets of entities, a KG commonly contains some dangling
entities that cannot find counterparts in other KGs. Therefore, dangling-aware
entity alignment is more realistic than the conventional entity alignment where
prior studies simply ignore dangling entities. We propose a framework using
mixed high-order proximities on dangling-aware entity alignment. Our framework
utilizes both the local high-order proximity …

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