This repository is the official implementation of MetaTNE in our paper Node Classification on Graphs with Few-Shot Novel Labels via Meta Transformed Network Embedding.

We recommend first installing Anaconda3-5.2.0. Then, run the following commands to install requirements:

pip install -U pip && pip uninstall -y numpy && pip install --ignore-installed wrapt numpy==1.17.3 tensorflow-gpu==2.0.0 && pip install networkx==2.2 ray[tune]==0.8.3

To better understand our code, please familiarize yourself with the usage of Ray and Tune.

You can reproduce the results on BlogCatalog dataset as follows:

• Data Preparation

  python standardize_data.py --data BlogCatalog
  

• Training and Evaluation

  python run.py --dataset_str BlogCatalog --meta_num_pos_nodes 10 --meta_num_neg_nodes 20
  

  You may need to modify num_gpus and resources_per_trial according to your computing resources.

• Result Analysis

  python analysis.py --logdir ~/ray_results/BlogCatalog_10_20