Tagged articles

inductive learning

3 articles · Page 1 of 1

Jul 31, 2023 · Artificial Intelligence

Knowledge Graph based Graph Neural Network Reasoning: From KG Background to GNN for KG and KG for GNN

This article introduces the fundamentals of knowledge graphs, explains how graph neural networks can be adapted for knowledge graph reasoning, presents specialized GNN designs such as CompGCN and RED‑GNN, and discusses experimental results, interpretability, efficiency improvements, and future research directions.

Graph Neural NetworkKG reasoningRED-GNN

0 likes · 11 min read

Knowledge Graph based Graph Neural Network Reasoning: From KG Background to GNN for KG and KG for GNN

DataFunTalk

Jul 23, 2022 · Artificial Intelligence

Graph Algorithm Deployment and Practices on the DataFun Security Spark Cluster

This article presents a comprehensive overview of deploying and running graph learning algorithms—both inductive and transductive—on the secure Spark cluster, covering framework choices, data sampling strategies, distributed training techniques, model evaluation metrics, and future directions.

Distributed TrainingGraph AlgorithmsSpark

0 likes · 13 min read

Graph Algorithm Deployment and Practices on the DataFun Security Spark Cluster

Alibaba Cloud Developer

Aug 9, 2019 · Artificial Intelligence

How GATNE Advances Heterogeneous Graph Embedding with Edge Types and Node Features

This article introduces GATNE, a graph embedding framework that jointly models heterogeneous nodes, multiple edge types, and rich node attributes using base and edge embeddings, self‑attention, and inductive learning, and demonstrates its superior performance on several real‑world datasets.

GATNEgraph embeddingheterogeneous networks

0 likes · 8 min read

How GATNE Advances Heterogeneous Graph Embedding with Edge Types and Node Features