A Multi-view Knowledge Graph Embedding Model Considering Structure and Semantics
The essence of knowledge representation learning is to embed the knowledge graph into a
low-dimensional vector space to make knowledge computable and deductible. Semantic …
low-dimensional vector space to make knowledge computable and deductible. Semantic …
Binarized Attributed Network Embedding via Neural Networks
H Xia, N Gao, J Peng, J Mo… - 2020 International Joint …, 2020 - ieeexplore.ieee.org
Traditional attributed network embedding methods are designed to map structural and
attribute information of networks jointly into a continuous Euclidean space, while recently a …
attribute information of networks jointly into a continuous Euclidean space, while recently a …