Extractive summarization

We all get buried in text. Sometimes we just want the main points without spending an hour reading. Extractive summarization is one way artificial intelligence (AI) tries to help.

The quick cut

She looks through a pile of words and picks sentences that matter most. No rewriting, no fancy paraphrasing. Just grab the good stuff and stitch it together. The result is shorter but still in the author’s own words.

How she scores

To decide which sentences make the cut, she assigns scores. Think word frequency, sentence position, or whether a phrase keeps showing up. Higher score means higher chance it survives. It’s a bit like grading homework with a rubric—mechanical, but it works.

Ranking the stack

After scoring, she ranks sentences. Top ones stay, the rest get tossed. The trick is to keep enough variety so the summary doesn’t repeat itself. If all the winners say the same thing, we don’t gain much. Ranking makes sure we hear the essentials without the echo.

Where it helps

We see it in news feeds, research abstracts, even customer reviews. Anywhere too much text slows us down. Extractive summarization is quick and cheap compared to fancier methods, though sometimes it feels rough around the edges. Good enough for scanning; not always smooth for storytelling.

A coder’s thought

We like the blunt honesty of it. She doesn’t pretend to be a poet. She just picks sentences and lines them up. It’s like duct tape for words—plain, functional, and usually strong enough.