The final, formatted version of the article will be published soon. Background Biomedical knowledge graphs (KGs), such as the Data Distillery Knowledge Graph (DDKG), capture known relationships among ...
Abstract: Graph Convolutional neural Networks (GCNs) demonstrate exceptional effectiveness when working with data that have non-Euclidean structures. In recent years, numerous researchers have ...
Predicting Links in Knowledge Graphs With the Canonical Correlation Analysis and Fusing Tensor Model
Abstract: Relation prediction in knowledge graphs is critical for uncovering missing links between entities. Previous models mostly focused on learning the distance of entities and relation within ...
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