JRC1995/TextRank-Keyword-Extraction

Keyword extraction using TextRank algorithm after pre-processing the text with lemmatization, filtering unwanted parts-of-speech and other techniques.

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/ 100
Emerging

This project helps anyone who needs to quickly understand the core topics of a document by automatically extracting the most important keywords. You provide a piece of text, and it processes that text to identify and output a list of key terms. It's designed for researchers, analysts, or content creators who want to distill information efficiently.

112 stars. No commits in the last 6 months.

Use this if you have documents, articles, or reports and need a quick, unbiased way to identify their main subjects without reading the entire text.

Not ideal if you need to extract specific entities like names, organizations, or locations, or if you require a sentiment analysis of the text.

text-analysis information-extraction document-summarization content-analysis research-assist
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 9 / 25
Maturity 16 / 25
Community 21 / 25

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Stars

112

Forks

43

Language

Jupyter Notebook

License

MIT

Last pushed

Feb 04, 2020

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/nlp/JRC1995/TextRank-Keyword-Extraction"

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