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 ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback