stdlib-js/nlp-lda
Latent Dirichlet Allocation via collapsed Gibbs sampling.
This tool helps you uncover hidden themes or topics within a collection of text documents, like surveys, articles, or speeches. You provide a set of documents and specify how many topics you expect to find. The output shows you the most important words for each identified topic, helping you understand the key subjects being discussed across your content. It's designed for data analysts, researchers, or anyone working with large text datasets to distill meaningful insights.
Use this if you need to automatically identify the main subjects or themes within a large body of text and understand which words are most associated with each theme.
Not ideal if you need to classify documents into pre-defined categories, as this tool discovers topics without prior labels.
Stars
9
Forks
—
Language
JavaScript
License
Apache-2.0
Category
Last pushed
Mar 04, 2026
Commits (30d)
0
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