taranis-story-clustering 0.5.1

Story Clustering Bot for Taranis-NG

Story Clustering

This code takes newsitems in the format as provided by Taranis-NG and clusters them into Stories.

Description and Use

The approach supports the following functionalities:

1. Automatically detect Events.
2. News items are clustered based on the detected Events.
3. Documents belonging to related Events are then clustered into Stories.

Initial clustering

The method initial_clustering in clustering.py takes as input a dictionary of news_items_aggregate (see tests/testdapa.py for the actual input format) and outputs a dictionary containing two keys: ("event_clusters" : list of list of documents ids) and ("story_clusters" : list of list of documents ids)

Incremental clustering

The incremental clustering method takes as input a dictionary of news_items_aggregate, containing new news items to be clustered, and clustered_news_items_aggregate, containing already clustered items, and tries to cluster the new documents to the existing clusters or create new ones. See tests/testdata.py for the actual input formats. This method also outputs a dictionary containing two keys: ("event_clusters" : list of list of documents ids) and ("story_clusters" : list of list of documents ids)

Installation

The requirements.txt file should list all Python libraries that the story-clustering depends on, and they will be installed using:

pip install .

Development

pip install .[dev]

Use

See notebook\test_story_clustering.ipynb for examples on how to use the clustering methods.

License

EUROPEAN UNION PUBLIC LICENCE v. 1.2