/coresetconstruction

Repository containing code and databases for experimental analysis of the ranged k-median algorithm presented in the master thesis "Range-Centric Coresets in Dynamic Geometric Streams"

Primary LanguagePythonMIT LicenseMIT

Range-Centric Coresets in Dynamic Geometric Streams

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".

Table of Contents

Overview

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.

Repository Structure

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/

Installation

To set up the environment and install the necessary dependencies, follow these steps:

  1. Clone the repository.
  2. Create a virtual environment.
  3. Install dependencies using requirements.txt

Datasets

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.

License

This project is licensed under the MIT license. See the LICENSE file for more details.

Contact

For any questions or inquiries, please contact Sam Nijsten.