KG provides a promising way to fuse multiple data sources by bridging the semantic gaps, which can be exploited in the modelling of a multi-faceted phenomenon.

In this study, with the aim of multi-source data integration by KGs, an approach based on GCN is proposed to learn representations of KGs for the multi-faceted ...

Oct 22, 2024 · The relevant information obtained from multiple sources usually contributes to one intricate phenomenon in the industrial processes.

Lastly, with the aim of multi-faceted conceptual modelling, the features obtained from the GCN model were used as inputs for machine learning algorithms to ...

Secondly, the KGs were fed into a graph convolutional neural network (GCN) to learn the node features and the graph structure for graph embedding simultaneously ...

Exploiting Knowledge Graph for Multi-faceted Conceptual Modelling using GCN ... Authors: Yuwei Wan; Zhenyuan Chen; Fu Hu; Ying Liu; Michael Packianather; Rui Wang ...

Exploiting Knowledge Graph for Multi-faceted Conceptual Modelling using GCN. Y. Wan, Z. Chen, F. Hu, Y. Liu, M. Packianather, and R. Wang.

Speaker: Yuwei Wan. Exploiting Knowledge Graph for Multi-faceted Conceptual Modelling using GCN. 5 views · 2 years ago ...more ...

Exploiting knowledge graph for multi-faceted conceptual modelling using GCN. Y Wan, Z Chen, F Hu, Y Liu, M Packianather, R Wang. Procedia Computer Science 200 ...