Text Summarizer
Extract and summarize key sentences from long text
Input Information
Result
Text Summarizer is an extractive summarization tool that automatically generates a concise summary by selecting only the key sentences from a long document or text. It picks the most important sentences from the original, so the meaning is not distorted and information is conveyed accurately.
It is very useful for quickly compressing news articles, paper abstracts, business reports, minutes, and blog posts. Especially handy for time-pressed professionals, students, journalists, and marketers, it runs right in the browser with no software installation.
It supports both Korean and English text and lets you adjust the summary length among short, medium, and long. The reduction ratio versus the original word count is also shown, so you can see efficiency at a glance. Not a full AI summary, but capable enough to quickly grasp key points for daily work and study.
It offers an intuitive interface — just paste text and see results immediately — and the summary can be copied to the clipboard with one click and pasted into other applications.
Term Glossary
- Extractive Summarization
- A method that gathers important sentences from the original as-is. Unlike abstractive summarization, it adds no content absent from the source.
- Stop Words
- Words with little actual meaning in a sentence — particles, articles, prepositions (e.g. 이, 가, the, a). Excluded when selecting key words for summarization.
- TF (Term Frequency)
- Short for Term Frequency — how often a word appears in the whole text. The more frequent, the more likely it is a key topic.
Detailed Summary Algorithm:
This tool uses a TF (Term Frequency) based sentence-scoring algorithm . A traditional and effective NLP summarization technique based on the principle that frequently appearing words represent the key topic.
Step 1 - Sentence splitting: Split the input text into individual sentences using periods (.), question marks (?), exclamation marks (!), Korean sentence-ending forms (da, yo, nida, etc.), and line breaks.
Step 2 - Preprocessing & stop-word removal: Lowercase each sentence and remove Korean particles/endings (i, ga, eul, reul, eun, neun, e, ui, etc.) and English articles/prepositions (the, a, is, of, in, etc.) using the stop-word list, leaving only meaningful key words.
Step 3 - Word frequency calculation: Count occurrences of all remaining words to compute each word’s frequency (TF). More frequent words get higher scores.
Step 4 - Sentence scoring: Sum the frequencies of key words in each sentence and divide by the sentence length (word count) to get the average score per sentence. Score = (sum of key-word frequencies) / (sentence word count).
Step 5 - Select & sort top sentences: Select the top N sentences by score, then re-sort them in original text order to produce a naturally flowing summary.
Summary length criteria: Short = 2 sentences, Medium = about 30% of all sentences, Long = about 50%. If the input is 2 sentences or fewer, the original is returned unchanged.
Effective Usage and Tips:
1. Enter a sufficient amount of text
At least 3 sentences are needed for a meaningful summary; 1–2 sentences are returned unchanged. Prefer 10+ sentences for more accurate results.
2. Choose summary length to fit your purpose
Pick "Short" for quick checks, "Medium" for general summaries, "Long" for detailed ones. "Medium" (~30% of the original) gives the most balanced result.
3. More effective on single-topic text
News articles, papers, and reports focused on one topic yield higher quality. Mixed-topic text is better summarized per topic.
4. Understand extractive summarization
This tool extracts key sentences from the original (extractive). Unlike abstractive summarization that generates new sentences, it adds no new content, guaranteeing accuracy.
5. Summarize multiple times to compare
Running the same text with different lengths may select different key sentences. Pick the most suitable one for your need.
6. Reuse the summary
Use the copy button to paste the summary into email, notes, or documents. Linking it to a prompt generator or translator makes it even more efficient.
7. Works for both Korean and English
It works for both Korean and English, with stop-word lists optimized for both. Mixed text is supported, but single-language text gives the best quality.