qz-wang/cfane

Code for paper Unsupervised Attributed Network Embedding via Cross Fusion (WSDM 2021)

CFANE

implementation of paper Unsupervised Attributed Network Embedding via Cross Fusion (WSDM 2021)

Requirements

• python >= 3.6
• pytorch >= 1.4
• network >= 1.11

Usage

For default parameters, use following command

python train.py

If you want to use other parameter setting and dataset, you can use following command for optional arguments description.

python train.py -h

Repository contents

file	description
train.py	The main training code
model.py	The implementation of CFANE
aggregators.py	Aggregators for information propagation
utils.py	Data loading
node2vec.py	Generating random walk contexts. Refer to: https://github.com/aditya-grover/node2vec

Datasets

We provide Cora dataset and partitions of its ego-network as example of data format.

Our ego-network partition refers to https://github.com/google-research/google-research/tree/master/graph_embedding/persona