Graph Representation Learning
by 수현 김
1. Data & Fields
1.1. Social Media
1.2. Healthcare
1.3. Natural Science
1.4. Manufacture Engineering
1.5. NLP
1.6. GIS
1.7. Web Architecture
1.8. Data Visualization
2. Embedding (sub)graphs
2.1. Graph neural network
2.2. Graph Convolutional Network
2.3. GraphSAGE
2.4. Graph Attention Network
3. Graph Generation
3.1. GraphRNN
3.2. NetGAN
4. Basic Terminology
4.1. Node/Edge
4.2. Degree
4.3. Subgraph
4.4. Walk/Path/Circuit/Cycle
5. Graph Types
5.1. Directed/Undirected graph
5.2. Bipartite graph
5.3. Complete graph
5.4. Path graph
5.5. Cycle graph
5.6. Grid graph
6. Embedding nodes
6.1. Random walk
6.1.1. DeepWalk
6.1.2. LINE
6.1.3. node2vec
6.2. Matrix Factorization
6.2.1. Laplacian Eigenmaps
6.2.2. Graph Factorization
6.2.3. GraRep
6.2.4. HOPE