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Text Summarizer

Paste any article or document - get an extractive summary using TF-IDF scoring. No API, works fully in your browser.

Input Text
Summary

Summary will appear here after clicking "Summarize".

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Text Summarization FAQ

Extractive summarization selects the most important original sentences and assembles them into a summary - no new text is generated. Abstractive summarization (used by LLMs like ChatGPT) paraphrases and generates new sentences. Extractive is deterministic and never fabricates content; abstractive is more fluent but can hallucinate. This tool uses extractive TF-IDF scoring.

TF-IDF (Term Frequency–Inverse Document Frequency) scores words by how often they appear in a sentence (TF) relative to how rarely they appear across all sentences (IDF). Words that are frequent in a sentence but rare in others are likely important to that sentence's meaning. Sentences with high TF-IDF scores are selected as the summary.

TF-IDF extractive summarization works best on news articles, academic papers, reports, and blog posts where key information is contained in well-formed sentences. It works less well on conversational text, bullet-point lists, or highly technical content with domain-specific jargon that appears throughout. For creative writing or dialogue, abstractive AI summarization gives better results.