Graph Embeddings
Large-scale Information Network Embedding
Introduced by Tang et al. in LINE: Large-scale Information Network EmbeddingLINE is a novel network embedding method which is suitable for arbitrary types of information networks: undirected, directed, and/or weighted. The method optimizes a carefully designed objective function that preserves both the local and global network structures.
Source: Tang et al.
Image source: Tang et al.
Source: LINE: Large-scale Information Network Embedding
Papers
| Paper | Code | Results | Date | Stars |
|---|
Tasks
| Task | Papers | Share |
|---|---|---|
| Graph Embedding | 5 | 33.33% |
| Link Prediction | 2 | 13.33% |
| Node Classification | 2 | 13.33% |
| Community Detection | 1 | 6.67% |
| Self-Supervised Learning | 1 | 6.67% |
| Chatbot | 1 | 6.67% |
| Decision Making | 1 | 6.67% |
| Recommendation Systems | 1 | 6.67% |
| Graph Sampling | 1 | 6.67% |
Usage Over Time
Components
| Component | Type |
|
|---|---|---|
| 🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |
