Stem Words in Text

The Stem Words in Text Tool shortens words to their roots by removing common suffixes. Choose between basic and aggressive stemming modes, with an option to preserve original casing. Quickly process large text blocks for search, indexing, or data preparation.

Paste your input above or import a file below.
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Supported file type: text/plain (.txt)
Options
Preserve Case

How to Use:

  1. Paste or enter your text into the Input Text box.
  2. In the Options section, select Basic Stemming or Aggressive Stemming.
  3. Toggle Preserve Case if you want the original capitalization to remain.
  4. The Stemmed Output will update automatically.
  5. Use Copy Output to copy the results or Export to File to download them.
  6. You can also import a .txt file using the Choose File button below the input box.

Feature Guide:

The Stem Words in Text Tool offers flexible control over how much stemming is applied to your text.

  • Basic Stemming removes simple endings like -ing, -ed, and -s.
  • Aggressive Stemming targets deeper suffixes like -tion, -ment, and -ness for shorter stems.
  • Preserve Case allows you to maintain original letter casing for cleaner output when capitalization matters. Combined, these options let you prepare clean, normalized text for indexing, keyword analysis, or machine learning.

Example:

Input:
Running faster and jumped higher. Exciting competitions bring enjoyment and excitement.

Basic Stemming Output:
Runn faster and jump higher. Excit competition bring enjoyment and excitement.

Aggressive Stemming Output:
Runn faster and jump higher. Excit competi bring enjoy and excit.

Common Use Cases:

The Stem Words in Text Tool helps when you need to normalize word forms for text analysis, search engine indexing, or preparing data for machine learning. By trimming words to their roots, it reduces redundancy and improves the consistency of large datasets without needing full linguistic parsing.

Useful Tools & Suggestions:

After stemming your words, Lemmatize Text can refine them further by pulling each one back to its proper dictionary form. And if you’re prepping for visualization or frequency analysis, Tokenize Text makes it easy to break everything down cleanly before you dive in.

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