Learning knowledge graph embedding with heterogeneous relation attention networks
Knowledge graph (KG) embedding aims to study the embedding representation to retain the
inherent structure of KGs. Graph neural networks (GNNs), as an effective graph …
inherent structure of KGs. Graph neural networks (GNNs), as an effective graph …
Learning Knowledge Graph Embedding With Heterogeneous Relation Attention Networks.
Z Li, H Liu, Z Zhang, T Liu, NN Xiong - IEEE Transactions on Neural …, 2022 - europepmc.org
Knowledge graph (KG) embedding aims to study the embedding representation to retain the
inherent structure of KGs. Graph neural networks (GNNs), as an effective graph …
inherent structure of KGs. Graph neural networks (GNNs), as an effective graph …
[引用][C] Learning Knowledge Graph Embedding With Heterogeneous Relation Attention Networks
Z Li, H Liu, Z Zhang, T Liu, NN Xiong - IEEE Transactions on Neural …, 2022 - cir.nii.ac.jp
Learning Knowledge Graph Embedding With Heterogeneous Relation Attention Networks |
CiNii Research CiNii 国立情報学研究所 学術情報ナビゲータ[サイニィ] 詳細へ移動 検索フォームへ …
CiNii Research CiNii 国立情報学研究所 学術情報ナビゲータ[サイニィ] 詳細へ移動 検索フォームへ …
Learning Knowledge Graph Embedding With Heterogeneous Relation Attention Networks
Z Li, H Liu, Z Zhang, T Liu… - IEEE transactions on …, 2022 - pubmed.ncbi.nlm.nih.gov
Knowledge graph (KG) embedding aims to study the embedding representation to retain the
inherent structure of KGs. Graph neural networks (GNNs), as an effective graph …
inherent structure of KGs. Graph neural networks (GNNs), as an effective graph …