Wilson-ZHANG/GraphZoom

GraphZoom

GraphZoom is a framework that aims to improve both performance and scalability of graph embedding techniques.

Citation

If you use GraphZoom in your research, please cite our preliminary work published in ICLR'20.

    @inproceedings{deng2020graphzoom,
      title={GraphZoom: A Multi-level Spectral Approach for Accurate and Scalable Graph Embedding},
      author={Chenhui Deng and Zhiqiang Zhao and Yongyu Wang and Zhiru Zhang and Zhuo Feng},
      booktitle={International Conference on Learning Representations},
      year={2020},
      url={https://openreview.net/forum?id=r1lGO0EKDH}
    }

Requirements

• Matlab Compiler Runtime (MCR) 2018a(Linux), which is a standalone set of shared libraries that enables the execution of compiled MATLAB applications and does not require license to install.
• numpy
• networkx
• scipy
• scikit-learn
• gensim, only required by deepwalk, node2vec
• tensorflow, only required by graphsage

Installation

1. install matlab compiler runtime 2018a(Linux) (https://www.mathworks.com/products/compiler/matlab-runtime.html)
2. pip install -r requirements.txt

Usage

Note: You have to pass the root directory of matlab compiler runtime to the argument "--mcr_dir" when running graphzoom.py

Example Usage cd graphzoom

``python graphzoom.py --mcr_dir YOUR_MCR_ROOT_DIR --dataset citeseer --search_ratio 12 --num_neighs 10 --embed_method deepwalk``

--mcr_dir: root directory of matlab compiler runtime

--dataset: input dataset, currently supports "json" format

--embed_method: choose a specific basic embedding algorithm

--search_ratio: control the search space of graph fusion

--num_neighs: control number of edges in feature graph

Full Command List The full list of command line options is available with python graphzoom.py --help

Coarsening Code The matlab version of spectral coarsening code is available in mat_coarsen/