Awesome
CallMine
CallMine: Fraud Detection and Visualization of Million-Scale Call Graphs
Authors: Mirela Cazzolato<sup>1,2</sup>, Saranya Vijayakumar<sup>1</sup>, Meng-Chieh Lee<sup>1</sup>, Catalina Vajiac<sup>1</sup>, Namyong Park<sup>1</sup>, Pedro Fidalgo<sup>3,4</sup>, Agma J. M. Traina<sup>2</sup>, Christos Faloutsos<sup>1</sup>
Affiliations: <sup>1</sup> Carnegie Mellon University (CMU), <sup>2</sup> University of São Paulo (USP), <sup>3</sup> Mobileum, <sup>4</sup> ISCTE-IUL
Work accepted for publication at CIKM'2023
Setup environment
To create and use a virtual environment, type:
python -m venv wcw_venv
source wcw_venv/bin/activate
To install the requirements:
pip install -r requirements.txt
or simplymake prep
Usage:
Type make demo
to see a demo of CallMine and CallMine-Focus
Sample Dataset:
File INPUT_DATA/sample_raw_data.csv'
has a synthetic data sample with:
11,000 calls, consisting of
- 10,000 random calls:
- 2,000 sources
- 2,000 destinations
- 5 days
- Cluster with 1,000 calls
- 10 sources
- 10 destinations
- Phone calls with duration between 20 and 40 seconds