Recently there has been a series of studies in knowledge graph embedding...
Industry 4.0 and Internet of Things (IoT) technologies unlock unpreceden...
Many machine learning (ML) libraries are accessible online for ML
practi...
Graph self-supervised learning (SSL), including contrastive and generati...
Knowledge graphs (KG) are used in a wide range of applications. The
auto...
Graph neural networks (GNNs) have been widely adopted for semi-supervise...
Entity alignment, aiming to identify equivalent entities across differen...
Smart factories are equipped with machines that can sense their manufact...
Graph-based anomaly detection has been widely used for detecting malicio...
Entity alignment, aiming to identify equivalent entities across differen...
Graph Neural Networks (GNNs) have achieved promising performance in vari...
A prominent application of knowledge graph (KG) is document enrichment.
...
In a large-scale knowledge graph (KG), an entity is often described by a...
Knowledge bases (KBs) are not static entities: new information constantl...
Data exchange heavily relies on the notion of incomplete database instan...
Reusing published datasets on the Web is of great interest to researcher...
Reusing existing datasets is of considerable significance to researchers...
Real-time analytics that requires integration and aggregation of
heterog...
We study confidentiality enforcement in ontologies under the Controlled ...
Description Logic Knowledge and Action Bases (KABs) have been recently
i...