chinese-whispers 0.9.0
An implementation of the Chinese Whispers clustering algorithm.
License: MIT
Requires Python: ~=3.8
Keywords: graph clustering, unsupervised learning, chinese whispers, cluster analysis

# Chinese Whispers for Python

This is an implementation of the [Chinese Whispers](https://doi.org/10.3115/1654758.1654774) clustering algorithm in Python. Since this library is based on [NetworkX](https://networkx.github.io/), it is simple to use.

[![Unit Tests][github_tests_badge]][github_tests_link] [![Read the Docs][rtfd_badge]][rtfd_link] [![PyPI Version][pypi_badge]][pypi_link] [![Conda Version][conda_badge]][conda_link]

[github_tests_badge]: https://github.com/nlpub/chinese-whispers/actions/workflows/test.yml/badge.svg?branch=master
[github_tests_link]: https://github.com/nlpub/chinese-whispers/actions/workflows/test.yml
[rtfd_badge]: https://readthedocs.org/projects/chinese-whispers/badge/
[rtfd_link]: https://chinese-whispers.readthedocs.io/
[pypi_badge]: https://badge.fury.io/py/chinese-whispers.svg
[pypi_link]: https://pypi.python.org/pypi/chinese-whispers
[conda_badge]: https://anaconda.org/conda-forge/chinese-whispers/badges/version.svg
[conda_link]: https://anaconda.org/conda-forge/chinese-whispers

## Installation

- [pip](https://pip.pypa.io/): `pip install chinese-whispers`
- [Anaconda](https://docs.conda.io/en/latest/): `conda install conda-forge::chinese-whispers`

## Usage

Given a NetworkX graph `G`, this library can [cluster](https://en.wikipedia.org/wiki/Cluster_analysis) it using the following code:

```python
from chinese_whispers import chinese_whispers
chinese_whispers(G, weighting='top', iterations=20)
```

As the result, each node of the input graph is provided with the `label` attribute that stores the cluster label.

The library also offers a convenient command-line interface (CLI) for clustering graphs represented in the ABC tab-separated format (source`\t`target`\t`weight).

```shell
# Write karate_club.tsv (just as example)
python3 -c 'import networkx as nx; nx.write_weighted_edgelist(nx.karate_club_graph(), "karate_club.tsv", delimiter="\t")'

# Using as CLI
chinese-whispers karate_club.tsv

# Using as module (same CLI as above)
python3 -mchinese_whispers karate_club.tsv
```

A more complete usage example is available in the [example notebook](https://github.com/nlpub/chinese-whispers/blob/master/example.ipynb) and at <https://nlpub.github.io/chinese-whispers/>.

In case you require higher performance, please consider our Java implementation that also includes other graph clustering algorithms: <https://github.com/nlpub/watset-java>.

## Citation

* [Ustalov, D.](https://github.com/dustalov), [Panchenko, A.](https://github.com/alexanderpanchenko), [Biemann, C.](https://www.inf.uni-hamburg.de/en/inst/ab/lt/people/chris-biemann.html), [Ponzetto, S.P.](https://www.uni-mannheim.de/dws/people/professors/prof-dr-simone-paolo-ponzetto/): [Watset: Local-Global Graph Clustering with Applications in Sense and Frame Induction](https://doi.org/10.1162/COLI_a_00354). Computational Linguistics 45(3), 423&ndash;479 (2019)

```bibtex
@article{Ustalov:19:cl,
  author    = {Ustalov, Dmitry and Panchenko, Alexander and Biemann, Chris and Ponzetto, Simone Paolo},
  title     = {{Watset: Local-Global Graph Clustering with Applications in Sense and Frame Induction}},
  journal   = {Computational Linguistics},
  year      = {2019},
  volume    = {45},
  number    = {3},
  pages     = {423--479},
  doi       = {10.1162/COLI_a_00354},
  publisher = {MIT Press},
  issn      = {0891-2017},
  language  = {english},
}
```

## Copyright

Copyright (c) 2018&ndash;2024 [Dmitry Ustalov](https://github.com/dustalov). See [LICENSE](LICENSE) for details.