Knowledge Graph Entity Alignment with Graph Convolutional Networks: Lessons Learned

19 Nov 2019Max BerrendorfEvgeniy FaermanValentyn MelnychukVolker TrespThomas Seidl

In this work, we focus on the problem of entity alignment in Knowledge Graphs (KG) and we report on our experiences when applying a Graph Convolutional Network (GCN) based model for this task. Variants of GCN are used in multiple state-of-the-art approaches and therefore it is important to understand the specifics and limitations of GCN-based models... (read more)

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