goerlitz/nlp-topic-models
Application of topic models for topic extraction and similarity search
This project helps researchers and analysts quickly understand the main subjects within large collections of German text, such as political speeches or news articles. It takes in raw German text documents and identifies underlying themes, outputting a clear summary of the topics discussed and which texts relate to each topic. This is ideal for social scientists, linguists, or anyone needing to categorize and analyze extensive German language content.
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Use this if you need to automatically extract the primary subjects and concepts from a large volume of German documents.
Not ideal if your primary goal is sentiment analysis or if you are working exclusively with languages other than German.
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Jupyter Notebook
License
GPL-3.0
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Last pushed
Sep 01, 2020
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