Extract Keywords from Text

Automatically identify and extract the most significant words or phrases using advanced algorithms like RAKE.

Configuration

Input Text
Results
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Keyword Density

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Overused Words

Find word repetition.

Intelligent Text Mining

Stop guessing what your content is about. The Advanced Keyword Extractor goes beyond simple word counting. By leveraging the RAKE Algorithm, it identifies the most relevant concepts and phrases in your text, filtering out noise so you can focus on the signal. Whether you are an SEO professional optimizing specific pages or a student analyzing research papers, extracting the core topics is the first step to understanding.

RAKE vs. Frequency: Which to Use?

1. Frequency Analysis (Simple)

How it works: Counts how many times each word appears.

  • Good for: Word clouds, finding repetitive words, simple density checks.
  • Bad for: Finding multi-word topics (e.g., it sees "New York" as "New" and "York").

2. RAKE Algorithm (Smart)

How it works: Rapid Automatic Keyword Extraction. It looks for sequences of words that appear between "stop words" (like "and", "of", "the").

  • Good for: SEO research, YouTube tags, document tagging.
  • Why use it: It finds "New York City" as a single meaningful phrase.

RAKE Algorithm

Uses "Rapid Automatic Keyword Extraction" to find multi-word key phrases like "Artificial Intelligence" instead of just "Artificial".

N-Gram Control

Switch to Frequency mode and extract 1-word (Unigram), 2-word (Bigram), or 3-word (Trigram) sequences.

Export Data

Download your keyword analysis as a structured TXT, CSV or JSON file for further processing.

How to Extract Value

  • 1
    Choose Algorithm: Use RAKE for discovering topics/phrases. Use Frequency for word clouds or density checks.
  • 2
    Configure: Adjust the slider to see top 5, 10, or 50 keywords. Add custom stop words (e.g., "company, brand") to exclude them if they clutter your results.
  • 3
    Analyze: Look at the Score. High score in RAKE means the phrase is highly specific to this text (co-occurs frequently with relevant terms).
  • 4
    Export: Click "CSV" to save your research. Import this into Google Sheets or your favorite SEO tool.

What are N-Grams?

When using the Frequency mode, you will see options for "1-Word", "2-Word", etc. These are N-Grams.

Unigrams (1-Word)

Single words.
Example: "Data"

Bigrams (2-Words)

Two words appearing together.
Example: "Data Science"

Trigrams (3-Words)

Three words in sequence.
Example: "Data Science Course"

Common Use Cases

SEO Content Analysis

Analyze blog posts and articles to identify primary and secondary keywords. Use RAKE to find long-tail phrases that search engines love. Perfect for content optimization and meta tag generation.

YouTube Tag Generation

Paste your video script or description to extract relevant tags automatically. RAKE mode identifies specific, high-value phrases that improve video discoverability and ranking.

Academic Research

Extract key concepts from research papers and academic documents. Batch mode processes multiple abstracts at once. Perfect for literature reviews and identifying research themes.

Example

Input Text
Artificial intelligence and machine learning are transforming how businesses operate. Deep learning models can analyze massive datasets to find patterns humans might miss.
Extracted Keywords (RAKE)
deep learning modelsmachine learningartificial intelligencemassive datasetsbusinesses operate

Frequently Asked Questions

What is the RAKE algorithm?
RAKE (Rapid Automatic Keyword Extraction) is a famous algorithm that finds "Key Phrases" rather than just single words. It uses stop words (like "and", "the") as delimiters to split text into candidates and scores them based on word co-occurrence. This makes it ideal for identifying multi-word concepts that matter most in your content.
What is the difference between Frequency and RAKE?
Frequency counts how many times a word appears. RAKE calculates a relevance score based on word co-occurrence and context. RAKE is better for finding multi-word topics (e.g., "Machine Learning") even if they appear less often than generic words like "dataset". Use Frequency for simple word counts and RAKE for semantic analysis.
Can I extract two-word phrases (Bigrams)?
Yes! Switch the Algorithm to "Frequency" and select "2-Word" in the settings. This is perfect for identifying common pairings like "climate change" or "social media". You can also extract 3-word phrases (trigrams) for even more context.
What are Stop Words?
Stop words are common, low-value words (like "is", "at", "which", "the") that appear frequently but carry little semantic meaning. Our tool excludes them by default to focus on your content's actual meaning. You can also add your own custom stop words to filter out brand names or industry-specific terms.
How do I export the data?
Once your keywords are extracted, click the "TXT", "CSV" or "JSON" buttons at the top of the Results panel. TXT downloads a simple comma-separated list. CSV is perfect for Excel analysis. JSON is ideal for programmatic use or integration with other tools.
Is this tool free for commercial use?
Yes, this tool is 100% free for all users, including for commercial SEO analysis, content research, academic papers, and professional marketing campaigns. There are no hidden fees, usage limits, or premium tiers.
Does it work with non-English text?
The "Frequency" algorithm works with any language that uses spaces to separate words. RAKE is optimized for English but can work for other languages if you provide a custom list of stop words in that language. Spanish, French, German, and most European languages work well with proper stop words.
What is the "Score" column in RAKE results?
The score represents the word's degree (co-occurrence with other meaningful words) divided by its frequency. A higher score means the phrase is likely more significant and specific to this text. For example, "artificial intelligence" might score higher than "data" because it's more contextually relevant.
Can I use this for YouTube tags?
Absolutely. Paste your video script or description to generate high-relevance tags. We recommend using the "RAKE" mode to find specific long-tail tags that match your content's actual topics. This helps with video SEO and discoverability.
How accurate is the RAKE algorithm for different content types?
RAKE performs best on well-structured content like articles, blogs, research papers, and documentation. For short texts (tweets, reviews), simple frequency counting may work better. For technical content with jargon, adding domain-specific stop words improves accuracy significantly. Academic papers benefit most from RAKE as it identifies key research concepts.