yncui-nju / CLP

Transfer-and-Fusion: Integrated Link Prediction across Knowledge Graphs

Quick Start

Installation

Install PyTorch following the instructions on the PyTorch. Our code is written in Python3.

• pytorch=1.11.0
• pyg=2.0.4

conda install pytorch==1.11.0 torchvision==0.12.0 torchaudio==0.11.0 cudatoolkit=11.3 -c pytorch
conda install pyg -c pyg

Dataset

unzip dataset.zip

It will generate two dataset folders in the ./data directory. In our experiments, the datasets used are: DBP-FB and WIKI-YAGO. In each dataset, there are two KGs and shared entities between them.

Training and evaluation

python main.py -dataset <dataset_name> -gpu <device_id> 

In our experiments, the datasets used are: DBP-FB or WIKI-YAGO.