Keyword Extraction API - RAKE Keywords from Any Text avatar

Keyword Extraction API - RAKE Keywords from Any Text

Pricing

$20.00 / 1,000 text analyzeds

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Keyword Extraction API - RAKE Keywords from Any Text

Keyword Extraction API - RAKE Keywords from Any Text

Keyword extraction API using the RAKE algorithm. Input: text string(s). Output: JSON array of ranked keywords and multi-word phrases with relevance scores. No training data, no LLM, no API key. Ideal for tagging, SEO, and content pipelines. $0.02 per text analyzed.

Pricing

$20.00 / 1,000 text analyzeds

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0.0

(0)

Developer

Anthony Snider

Anthony Snider

Maintained by Community

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0

Bookmarked

2

Total users

1

Monthly active users

8 days ago

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Text Keyword Extractor

Extract the most important keywords and key phrases from any text using the RAKE algorithm — no training, no model, no external API. Perfect for tagging, SEO metadata, and content indexing.

Live on the Apify Store — run it instantly or call it as an agent tool via Apify MCP.

What you get

  • Key phrases ranked by RAKE score (word degree ÷ frequency, summed per phrase)
  • Top single words by frequency (stopwords removed)
  • Single text or bulk array of texts in one run
  • Pure deterministic, offline extraction — fast and private

Input

FieldTypeDescription
textstringThe text to analyze (or use texts)
textsarrayBulk list of texts, each analyzed independently
topNintegerHow many keywords / top words to return (default 20)
maxTextsintegerCap on texts per run (default 50)
{
"text": "Compatibility of systems of linear constraints over the set of natural numbers. Criteria of compatibility of a system of linear Diophantine equations are considered.",
"topN": 10
}

Output

One dataset item per text:

{
"text": "Compatibility of systems of linear constraints over the set of natural numbers...",
"keywords": [
{ "phrase": "linear diophantine equations", "score": 9.0 },
{ "phrase": "linear constraints", "score": 4.0 },
{ "phrase": "natural numbers", "score": 4.0 }
],
"topWords": [
{ "word": "linear", "count": 3 },
{ "word": "compatibility", "count": 2 }
],
"keywordCount": 10,
"uniqueWords": 14,
"candidatePhrases": 9
}