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Think Before You Discard: Accurate Triangle Counting in Graph Streams with Deletions

ThinkD is a streaming algorithm for triangle counting in a fully dynamic graph stream with edge additions and deletions. ThinkD estimates the counts of global triangles and local triangles by making a single pass over the stream. ThinkD has the following advantages:

  • Accurate: ThinkD is up to 4.3X more accurate than its best competitors within the same memory budget
  • Fast: ThinkD is up to 2.2X faster than its best competitors for the same accuracy requirements
  • Theoretically Sound: ThinkD always maintains unbiased estimates

Datasets

The download links for the datasets used in the paper are here

Building and Running WRS

Please see User Guide

Running Demo

For demo, please type 'make'

Reference

If you use this code as part of any published research, please acknowledge the following papers.

@inproceedings{shin2018think,
  title={Think before you discard: Accurate triangle counting in graph streams with deletions},
  author={Shin, Kijung and Kim, Jisu and Hooi, Bryan and Faloutsos, Christos},
  booktitle={Joint European Conference on Machine Learning and Knowledge Discovery in Databases},
  pages={141--157},
  year={2018},
  organization={Springer}
}

@article{shin2020fast,
  title={Fast, accurate and provable triangle counting in fully dynamic graph streams},
  author={Shin, Kijung and Oh, Sejoon and Kim, Jisu and Hooi, Bryan and Faloutsos, Christos},
  journal={ACM Transactions on Knowledge Discovery from Data (TKDD)},
  volume={14},
  number={2},
  pages={1--39},
  year={2020},
  publisher={ACM New York, NY, USA}
}