Amey-Thakur/TEXT-SUMMARIZER

Machine Learning Project to Compare and Evaluate Text Summarization Algorithms Using SpaCy, NLTK, Gensim, and Sumy.

50
/ 100
Established

This tool helps busy professionals quickly grasp the core ideas from lengthy texts or web articles. You input the original text or a URL, and it provides several concise summaries, comparing how different algorithms condense the information. It's ideal for anyone who needs to extract key insights without reading through entire documents.

Use this if you frequently need to get the main points from long articles, reports, or web pages and want to compare different summarization styles.

Not ideal if you need human-quality, interpretive summaries or wish to summarize highly specialized content where nuance is critical.

information-retrieval content-curation research-analysis reading-efficiency knowledge-management
No Package No Dependents
Maintenance 10 / 25
Adoption 7 / 25
Maturity 16 / 25
Community 17 / 25

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Stars

39

Forks

11

Language

HTML

License

MIT

Last pushed

Feb 20, 2026

Commits (30d)

0

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