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An Accurate Unsupervised Method for Joint Entity Alignment and Dangling Entity Detection
[article]
2022
arXiv
pre-print
Knowledge graph integration typically suffers from the widely existing dangling entities that cannot find alignment cross knowledge graphs (KGs). The dangling entity set is unavailable in most real-world scenarios, and manually mining the entity pairs that consist of entities with the same meaning is labor-consuming. In this paper, we propose a novel accurate Unsupervised method for joint Entity alignment (EA) and Dangling entity detection (DED), called UED. The UED mines the literal semantic
arXiv:2203.05147v1
fatcat:oesytag7brehtpdd7vq3eqwnvi