GBIM

This repository contains the source code of the AAAI-2024 paper "Graph Bayesian Optimization for Multiplex Influence Maximization"

Simply run the following command to test the GBIM in Multi-IC of the lastfm dataset with k=5.

python main.py

more data are in data.zip, you can download it from here and unzip it into ./data

To use these data, you need to first run

python datasample.py -d ciao -dm LT -k 5

to generate the initial training data D,

then run

python main.py -d ciao -dm LT -k 5

ciao is one dataset in [ciao, epinions, delicous, lastfm]

dm [LT, IC]

k is the seed set size

Please cite our paper if it is helpful to your work.

@inproceedings{yuan2024graph,
  title={Graph Bayesian Optimization for Multiplex Influence Maximization},
  author={Yuan, Zirui and Shao, Minglai and Chen, Zhiqian},
  booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
  volume={38},
  number={20},
  pages={22475--22483},
  year={2024}
}