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On Shapley Value in Data Assemblage Under Independent Utility

This repository contains the implementation of algorithms in our VLDB 2022 paper.

If you find the code here useful, please consider to cite our paper:

@article{PVLDB:shapley-value-under-independent-utility,
  author = {Luo, Xuan and Pei, Jian and Cong, Zicun and Xu, Cheng},
  title = {On Shapley Value in Data Assemblage Under Independent Utility},
  journal = {Proceedings of the VLDB Endowment},
  year = {2022},
  volume = {15},
  number = {11},
  pages = {2761--2773},
  issn = {2150-8097},
  doi = {10.14778/3551793.3551829}
}

Install Dependencies

  • OS: Ubuntu 20.04 LTS.
  • Rust: curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh

Build

cargo build --release

Source Data

Source data: https://drive.google.com/drive/folders/1cSQa4S_ughm7x8rOUljig59DcRQMVJL1?usp=sharing

How to Run

  1. Download source data
  2. Go to scripts folder, generate metadata via:
python3 assign_data.py -d dataset -a <alpha> -b <beta> -k <number_of_data_owner> -m <max_copy> -o <equal owners> -r <equal records> -f <output dir>

Example:

python3 assign_data.py -d 'world' -a 4 -b 3 -k 10 -m 3 -o 1 -r 1 -f tmp/
  1. Calculate Shapley value for all data owners:
shapley-value  -i <source data dir> -m <metadata dir/dataset> -d <dataset> -o <output file> -s <scheme>

Example:

./target/release/shapley-value  -i data/world -m metadata/world -d world -o proposed.json -s proposed