ActiveEA: Active Learning for Neural Entity Alignment

Entity Alignment (EA) aims to match equivalent entities across different Knowledge Graphs (KGs) and is an essential step of KG fusion. Current mainstream methods -- neural EA models -- rely on training with seed alignment, i.e., a set of pre-aligned entity pairs which are very costly to annotate. In...

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Veröffentlicht in:	arXiv.org 2021-10
Hauptverfasser:	Liu, Bing, Scells, Harrisen, Zuccon, Guido, Wen, Hua, Zhao, Genghong
Format:	Artikel
Sprache:	eng
Schlagworte:	Active learning Alignment Annotations Knowledge representation Learning Sampling Uncertainty
Online-Zugang:	Volltext
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