This version is for the WSDM 2019 paper.
Get the datasets from https://drive.google.com/drive/folders/1lY3pqpnUAK0H9Tgjyh7tlMVYy0gYPthC?usp=sharing
and extract under data/
:
- AIDS80nef
- AIDS700nef
- linux
- IMDBMulti
Get the pickle files (/save
) from https://drive.google.com/drive/folders/1Eusvi4_iOKM0AsO1LhxQFkY62kDEtuMq?usp=sharing
Get the result files (/result
) https://drive.google.com/drive/folders/1UXEGozaThjjuC-hnt4C7jn06L6I2Ra1v?usp=sharing
Install the following the tools and packages:
python3
: Assumepython3
by default (usepip3
to install packages).numpy
pandas
scipy
scikit-learn
tensorflow
(1.8.0 recommended)networkx==1.10
(NOT2.1
)beautifulsoup4
lxml
matplotlib
seaborn
colour
pytz
pygraphviz
. The following is an example set of installation commands (tested on Ubuntu 16.04)sudo apt-get install graphviz libgraphviz-dev pkg-config pip3 install pygraphviz --install-option="--include-path=/usr/include/graphviz" --install-option="--library-path=/usr/lib/graphviz/"
- Graph Edit Distance (GED):
graph-matching-toolkit
cd src && git clone https://github.com/yunshengb/graph-matching-toolkit.git
- Follow the instructions on https://github.com/yunshengb/graph-matching-toolkit to compile
java
- If you see red lines under
import
, marksrc
andmodel/Siamese
asSource Root
, so that PyCharm can find those files. - Mark
src/Siamese/logs
andsrc/Siamese/exp
asExcluded
, so that PyCharm won't spend time inspecting those logs.
The idea of creating config.py
is to avoid typing in command line arguments. Instead, we can modify a few parameters in config.py
and let the file handle the setting of the rest parameters via a bunch of if
else
statements. Then we can simply run python main.py
without the following --xxx
s.