CN PAM

Efficient complex network representation using prime numbers

Accompanying code for CN2023 submission, please do not redistribute.

The requirements for this project can be met by running:

pip -r requirements.txt

Python version used: Python 3.9.16

Data are expected to be downloaded in a folder named data, here on the top-level folder.

The datasets used can be downloaded all in one from here.

The pam_creation.py,utils.py, grakel_utils.py files, contain functionality code to support the proposed framework and facilitate the experiments.

The rest of the files are used to reproduce the results present in the article:

• The scalability_test.py reproduces the usability results presented in Section 3.1.
• The relation_prediction.py reproduces the results presented in Section 3.2.
• The graph_classification_with_gridsearch.py reproduces the graph-kernel comparison results presented in Section 3.3. In order to calculate the Deltas for the performance on time and accuracy you have to run the graph_classification_calculate_deltas.py. You can either run it as is, with the already calculated results (saved in gc_results.csv) or re-run the graph_classification_with_gridsearch.py script to generate the new results.

This will be updated.