Keyword Extractor Guide
A keyword extractor scans text and surfaces the most important words and phrases, giving you a quick map of what a document is actually about. SEO specialists use the output to refine target keyword lists, content strategists to tag and categorize articles, and researchers to summarize the focus of large corpora. The tool filters out common stop words and weighs terms by frequency and contextual prominence so the results reflect meaning rather than noise. It turns a wall of text into a ranked list you can act on. The extractor tokenizes your input, removes stop words such as the, and, and of, then computes term frequency for each remaining word. Optional TF-IDF scoring weighs each term against a background corpus so words that are rare overall but frequent in your text score higher. N-gram detection groups adjacent words into phrases, surfacing multi-word terms like machine learning that single-word analysis would miss. Results are sorted by score and can be filtered by length or minimum frequency.