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$\mu\text{KG}$: A Library for Multi-source Knowledge Graph Embeddings and Applications. (arXiv:2207.11442v2 [cs.CL] UPDATED)
cs.CL updates on arXiv.org arxiv.org
This paper presents $\mu\text{KG}$, an open-source Python library for
representation learning over knowledge graphs. $\mu\text{KG}$ supports joint
representation learning over multi-source knowledge graphs (and also a single
knowledge graph), multiple deep learning libraries (PyTorch and TensorFlow2),
multiple embedding tasks (link prediction, entity alignment, entity typing, and
multi-source link prediction), and multiple parallel computing modes
(multi-process and multi-GPU computing). It currently implements 26 popular
knowledge graph embedding models and supports 16 benchmark datasets.
$\mu\text{KG}$ provides advanced implementations of embedding techniques with …
applications arxiv graph knowledge knowledge graph library text