vi3k6i5/GuidedLDA

semi supervised guided topic model with custom guidedLDA

52
/ 100
Established

This helps analysts and researchers organize large collections of text documents by automatically identifying key themes. You provide a collection of documents (like news articles or customer feedback) and, optionally, some keywords to guide the topic discovery. It outputs a set of identified topics and shows which documents relate to which topics. Anyone working with unstructured text data to find patterns or insights would find this useful.

517 stars. No commits in the last 6 months.

Use this if you need to extract meaningful topics from a large body of text and want to influence the topic generation process with your domain knowledge.

Not ideal if you are working with extremely large document corpuses (millions of documents) and require the absolute fastest performance, in which case more specialized tools might be better.

text-analysis content-categorization research-analysis document-management information-extraction
Stale 6m No Package No Dependents
Maintenance 2 / 25
Adoption 10 / 25
Maturity 16 / 25
Community 24 / 25

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Stars

517

Forks

112

Language

Python

License

MPL-2.0

Last pushed

Apr 14, 2025

Commits (30d)

0

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