Pierre Monnin

Discovering alignment relations with Graph Convolutional Networks: a\n biomedical case study

2020 · arXiv (Cornell University)

Knowledge graphs are freely aggregated, published, and edited in the Web of\ndata, and thus may overlap. Hence, a key task resides in aligning (or matching)\ntheir content. This task encompasses the identification, within an aggregated\nknowledge graph, …

Schema First! Learn Versatile Knowledge Graph Embeddings by Capturing Semantics with MASCHInE

2023 · arXiv (Cornell University)

Knowledge graph embedding models (KGEMs) have gained considerable traction in recent years. These models learn a vector representation of knowledge graph entities and relations, a.k.a. knowledge graph embeddings (KGEs). Learning versatile KGEs is desirable as …