Build a simple GNN for dictionary creation

[janetzki]

(https://towardsdatascience.com/graph-neural-networks-with-pyg-on-node-classification-link-prediction-and-anomaly-detection-14aa38fe1275)

Goal

There is a GNN model that links LRL words with semantic domains. Motivation: build GNN -> increase DC precision and recall > 0.30

Tasks

• [x] #18

Notes

• Some ideas to get started
  • Re-implement https://medium.com/p/c71f6f61ff0f
  • https://github.com/plkmo/Bible_Text_GCN
  • use text-GCN for document classification for each of the 1189 chapters of the Bible
  • 66 labels = 66 books
  • each document-word and word-word edges has predetermined weights
    • eg tf-idf
  • chapter-word edges encode context within chapter
  • word-word edges encode relative context between chapters
  • https://miro.medium.com/max/1400/1*R2IFb9Q8HhtVlyxUa_cy3g.png
  • GNN: https://github.com/danielegrattarola/spektral
  • GNN: https://github.com/benedekrozemberczki/SimGNN
  • Try out https://github.com/pyg-team/pytorch_geometric
  • google "keras graph neural network (colab/notebook)"
  • if needed: get inspiration at https://paperswithcode.com/search?q_meta=&q_type=&q=graph+neural+networks+keras