FATNet

This is a TensorFlow implementation of of Fusing Attributed and Topological Global-Relations for Network Embedding.

Requirements

• tensorflow (>0.14)

Preprocess data

Run the walk.py for data preprocessing.

Run experiments

python train_cora.py

Data

In order to use your own data, you have to provide

• an N by N adjacency matrix (N is the number of nodes),
• an N by D feature matrix (D is the number of features per node), and
• an N by E binary label matrix (E is the number of classes).
• walk file(you can use walks.py to generate).

Tips

Please create the following log folders in this project directory.

./Log/cora
./Log/citeseer
./Log/wiki
./Log/pubmed
./Log/blogcatalog