This project aims to explore different methods of performing node classification and link prediction using the CORA graph dataset. Specifically, we compare the performance of GraphSAGE and GCN models ...

Graph Neural Networks GNNs are advanced tools for graph classification, leveraging neighborhood aggregation to update node representations iteratively. This process captures local and global graph ...

Therefore, link prediction problems in the original graph can be equivalently solved as a node classification problem in its corresponding line graph, instead of a graph classification task.

This paper discusses the application of knowledge graph in complex network analysis, especially for the two key tasks of node classification and link prediction. The framework of this paper combines ...

Furthermore, graph embedding methods are able to generate embeddings that can be used for multiple downstream tasks, such as link prediction, node classification, clustering, or visualization. Add ...

This project aims to explore different methods of performing node classification and link prediction using the CORA graph dataset. Specifically, we compare the performance of GraphSAGE and GCN models ...