andifunke/topic-labeling
The project proposes a framework to apply topic models on a text-corpus and eventually topic labels on the generated topics.
This tool helps researchers, data analysts, or content strategists understand the main themes within large collections of German text documents, such as news articles or political speeches. You provide raw German text data, and the tool identifies underlying topics and assigns clear, descriptive labels to each topic. This helps you quickly grasp what your documents are about without manually reading through everything.
Use this if you need to automatically identify the key topics in a large dataset of German texts and get clear, human-readable labels for those topics.
Not ideal if your primary goal is to analyze text in languages other than German, or if you only need simple keyword extraction without topic modeling and labeling.
Stars
36
Forks
8
Language
Jupyter Notebook
License
Apache-2.0
Category
Last pushed
Mar 15, 2026
Commits (30d)
0
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