liminfoText Summarizer
Free web tool: Text Summarizer
Usage Guide
- Uses extractive summarization to select important sentences from the original text.
- Calculates sentence importance based on word frequency.
- Supports both Korean and English text.
- All processing is done in the browser. No data is sent to the server.
About Text Summarizer
The Text Summarizer uses extractive summarization — an NLP technique that selects the most important sentences from the original text rather than generating new ones. Unlike AI-based summarizers that require cloud API calls, this tool runs entirely in your browser using a word frequency scoring algorithm. It tokenizes the input text into sentences, builds a word frequency map (excluding common English and Korean stop words), scores each sentence based on the normalized frequency of its content words, applies a slight position boost to early sentences, and returns the top N sentences in their original order.
This tool is useful for quickly extracting key points from long articles, research papers, meeting notes, or news stories. Journalists and researchers use it to get a quick overview before committing to a full read. Students use it to review dense academic texts. Content teams use it to generate candidate social media summaries from blog posts. The tool supports both English and Korean text in the same session, making it valuable for bilingual workflows.
The extractive algorithm works as follows: (1) the text is split into sentences using a regex that matches sentence-ending punctuation, (2) words are extracted and lowercased after stripping non-letter/non-number characters, (3) common stop words in both English (100+ words) and Korean (30+ particles and auxiliaries) are excluded from the frequency count, (4) each word's frequency is normalized by the maximum frequency in the document, (5) each sentence receives a score = sum of normalized word frequencies / sentence word count, with a position boost of up to 20% for earlier sentences, (6) the top N sentences by score are selected and re-sorted by their original position in the text.
Key Features
- Extractive summarization — selects the most important original sentences without hallucination or paraphrasing
- Adjustable summary length: choose 3, 5, 7, or 10 output sentences based on your needs
- Supports both English and Korean text, with language-appropriate stop word lists for both
- Word frequency scoring with normalization — avoids bias toward artificially long sentences
- Position-weighted scoring gives a slight preference to sentences appearing earlier in the text
- Character and word count display for both input and output to track compression ratio
- One-click copy of the summary result to clipboard
- 100% client-side processing — your text is never sent to any server or API
Frequently Asked Questions
What is extractive summarization and how does it differ from AI summarization?
Extractive summarization selects and returns actual sentences from the original text that are scored as most important. The output contains only words that appeared in the input — there is no paraphrasing or generation of new content. AI-based (abstractive) summarization, by contrast, generates new sentences that may paraphrase or combine information from multiple parts of the text. Extractive summarization is deterministic (same input always gives the same output), does not hallucinate, and requires no cloud API or subscription.
How does the word frequency scoring algorithm work?
The algorithm: (1) splits text into sentences on punctuation boundaries, (2) builds a word frequency map from all words in the text, excluding common stop words in both English and Korean, (3) normalizes each word frequency by dividing by the highest frequency in the document, (4) scores each sentence as the mean of the normalized frequencies of its content words, (5) applies a position boost — sentences that appear earlier get up to 20% additional score — to reflect that topic sentences and key information often appear at the beginning of paragraphs and articles, (6) selects the top N sentences and returns them in their original document order.
Why are some important sentences not included in the summary?
The algorithm scores sentences based on how many high-frequency (important) words they contain relative to their length. Sentences that introduce new terminology, provide context, or use unique words may receive low scores even if they are subjectively important. The algorithm is a heuristic and works best on well-structured text where important concepts are repeated across multiple sentences. For texts with very uniform word frequency distributions, the results may be less distinctive.
What is the minimum text length required?
The tool requires at least 50 characters of input text. This minimum ensures there is enough content to meaningfully split into sentences and score. Very short texts (under 50 characters) are typically a single sentence and cannot be summarized — the tool will display an error message in this case.
Does the tool support languages other than English and Korean?
The tool will process any text that uses standard punctuation (periods, exclamation marks, question marks) as sentence boundaries. The stop word lists cover English and Korean specifically, so other languages will still produce output but may not filter stop words as effectively. For European languages that share similar stop words with English (articles, prepositions, conjunctions), the quality should still be reasonable.
Why does the summary sometimes include fewer sentences than I selected?
If the input text has fewer total sentences than the requested number (e.g., the text has 3 sentences but you requested 5), the tool returns all available sentences as the summary. The output cannot contain more sentences than exist in the input.
Is my text sent to any server or AI API?
No. All text processing happens entirely within your web browser. The tokenization, word frequency calculation, sentence scoring, and output generation are all performed by JavaScript running locally on your device. Your text never leaves your browser, is never stored, and is never sent to any server, AI API, or third party. This makes the tool suitable for summarizing confidential documents, internal reports, or sensitive research.
How should I choose the number of summary sentences?
As a general guideline: 3 sentences works well for articles up to 500 words (capturing the main point and two supporting ideas), 5 sentences is suitable for 500-1500 word articles, 7 sentences handles medium-length documents (1500-3000 words), and 10 sentences is appropriate for longer documents or when you need a more complete overview. The optimal setting depends on how much information density the source text contains and how much of the detail you want to preserve.