Covers: theory of Mixed-method Link Prediction
Estimated time needed to finish: 20 minutes
Questions this item addresses:
  • How can graph classification be used to predict links?
How to use this item?

This notebook covers:

  • Introduction to SEAL framework for link prediction
  • Creating Induced Subgraphs
  • Classification of Graphs using GNNs
Author(s) / creator(s) / reference(s)
Karim Khayrat
Programming Languages: PyTorch
0 comment

Link Prediction using Graph Neural Networks

Total time needed: ~1 hour
This recipe will walk you through the typical techniques used for predicting relationships between entities
Potential Use Cases
recommendation systems, friend suggestion on social media
Who is This For ?
INTERMEDIATEData Scientists, Machine Learning Engineers
Click on each of the following annotated items to see details.
Resource Asset3/3
REPO 1. Link Prediction as Graph Prediction
  • How can graph classification be used to predict links?
20 minutes
REPO 2. Embedding Based Link Prediction
  • How graph auto-encoder can be used to predict links?
20 minutes
PAPER 3. Review on Learning and Extracting Graph Features for Link Prediction
  • What are the ways link prediction work?
20 minutes

Concepts Covered

0 comment