lejon/PartiallyCollapsedLDA

Implementations of various fast parallelized samplers for LDA, including Partially Collapsed LDA, Light LDA, Partially Collapsed Light LDA and a very efficient Polya-Urn LDA

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Emerging

This tool helps researchers and data analysts understand large collections of text documents by identifying underlying themes or topics. You provide a dataset of texts, and it outputs statistical models of topics, showing which words are associated with each topic. This allows you to discover hidden structures and meaning within unstructured text, often used by social scientists, market researchers, or anyone working with extensive document archives.

No commits in the last 6 months.

Use this if you need to extract and analyze recurring themes or subjects from a large corpus of text documents efficiently and with advanced statistical controls.

Not ideal if you're looking for a simple, out-of-the-box solution without needing to configure advanced parameters or if you have only a small number of documents.

topic-modeling text-analysis natural-language-processing content-discovery information-retrieval
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 7 / 25
Maturity 8 / 25
Community 19 / 25

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Stars

28

Forks

22

Language

Java

License

Last pushed

Feb 12, 2023

Commits (30d)

0

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