This repository contains the code and databases used for the experimental analysis of the ranged k-median algorithm presented in the master thesis "Range-Centric Coresets in Dynamic Geometric Streams".
This repository implements the ranged k-median algorithm presented in the master thesis "Range-Centric Coresets in Dynamic Geometric Streams". The experiments are conducted on three datasets: blobs, Twitter, and Gowalla.
CoresetConstruction/
├── README.md
├── LICENSE
├── requirements.txt
├── src/
│ ├── CoresetConstruction.py
│ ├── PreProcessing.py
│ ├── RangedCoresetConstruction.py
│ ├── blobs.py
│ ├── cell.py
│ ├── gowalla.py
│ ├── kmedian.py
│ ├── twitter.py
│ └── visualize.py
├── datasets/
├── Gowalla/
└── Twitter/
To set up the environment and install the necessary dependencies, follow these steps:
- Clone the repository.
- Create a virtual environment.
- Install dependencies using requirements.txt
The experiments are conducted on the following datasets:
- Blobs: Synthetic data generated using Gaussian blobs.
- Twitter: Real-world Twitter data.
- Gowalla: Real-world Gowalla check-in data.
The datasets are stored in the datasets/ directory.
This project is licensed under the MIT license. See the LICENSE file for more details.
For any questions or inquiries, please contact Sam Nijsten.