/GenMeanDSG

Code and experimental results for the general mean densest subgraph problem

Primary LanguageMATLABMIT LicenseMIT

GenMeanDSG

Algorithmic implementations and code for experimental results from the paper

The Generalized Mean Densest Subgraph Problem
Nate Veldt, Austin Benson, Jon Kleinberg
KDD 2021

(https://arxiv.org/abs/2106.00909)

Data

The peeling algorithms experiments use publicly available graphs mostly from the SNAP repository (https://snap.stanford.edu/data/index.html), and can also be downloaded in .mat form from the SuiteSparse Matrix collection (https://sparse.tamu.edu/).

In order to run all experiments, many of the larger datasets will need to be downloaded and placed in the data folder.

FB100 graphs are also not included in the repo and will need to be added to the data folder in order to run experiments on these graphs.

Experiments

Optimal vs. greedy solutions

In order to obtain exact solutions to the p-mean densest subgraph objective, we implement our algorithm in MATLAB in order to use existing submodular function optimization software SFO (https://dl.acm.org/doi/10.5555/1756006.1756044).

See the Exp-Optimal folder.

Greedy peeling experiments on large networks

See the Exp-Peeling folder.

Facebook peeling experiments

See the Exp-Facebook folder.