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Text Summarizer

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About Text Summarizer

The Text Summarizer condenses long articles, essays, reports, and documents into the most important sentences using extractive summarization. Choose between two proven algorithms — Frequency-based and TextRank — and set the exact number of output sentences you need.

Frequency-based summarization scores each sentence by the total frequency of its significant words, favouring sentences that contain the most commonly used terms. TextRank builds a similarity graph of all sentences and applies a PageRank-style algorithm to identify the sentences most connected to the overall text — ideal for narrative articles and essays.

All processing happens in your browser using the same algorithms as the popular node-summarizer library. Your text never leaves your device.

How to Use Text Summarizer

  1. Paste or type your text into the input panel — articles, essays, or any long-form content work best.

  2. Choose a summarization method: Frequency (fast, keyword-driven) or TextRank (graph-based, better for narratives).

  3. Select how many sentences the summary should contain, then click the arrow to summarize.

  4. Copy the summary or review the sentence relevance chart to understand which sentences scored highest.

Examples

Example — Short paragraph
Input
The quick brown fox jumps over the lazy dog. Dogs are known for their loyalty and companionship. Foxes are clever animals that adapt well to many environments. The relationship between foxes and dogs in the wild is often one of competition.
Output
Foxes are clever animals that adapt well to many environments. The relationship between foxes and dogs in the wild is often one of competition.

Frequently Asked Questions

What is the difference between Frequency and TextRank?

Frequency-based summarization selects sentences containing the most frequently occurring significant words. TextRank builds a graph where sentences are nodes and shared vocabulary creates weighted edges — sentences that are most similar to the rest of the text rank highest. TextRank generally produces more coherent summaries for news articles and essays.

Is this extractive or abstractive summarization?

Extractive — the tool selects and returns actual sentences from the original text, without rewriting or paraphrasing. This means the summary is always factually accurate and uses the author's own words.

How much text do I need for a good summary?

At least 5–8 sentences (roughly 100–150 words) are needed for meaningful results. The more text you provide, the better the summary quality, since the algorithms have more sentences to compare and rank.

Does my text get sent to a server?

No — all summarization runs entirely in your browser using JavaScript. Your text never leaves your device.

What is the node-summarizer library?

node-summarizer is a Node.js package that implements frequency-based and TextRank extractive summarization. This tool uses the same algorithms, reimplemented to run directly in the browser without any server or installation required.