Enhancing Knowledge Graph Embedding by Composite Neighbors for Link Prediction

Source code for paper: Enhancing Knowledge Graph Embedding by Composite Neighbors for Link Prediction

Dependencies

• Compatible with PyTorch 1.0 and Python 3.x.
• Dependencies can be installed using requirements.txt.

Dataset:

• We use FB15k-237 and WN18RR dataset for knowledge graph link prediction.
• FB15k-237 and WN18RR are included in the data directory. The provided code is only for link prediction task

Training model:

• Install all the requirements from requirements.txt.

• Execute utils\\buildNeiData for extracting the composite neighbor data for dataset.

• To pretrain KGE decoder, execute pretrain.py and the embedding files are stored in save\\

• To start training run: main.py loading pre-trained embedding files