No API fees · Runs on your device · TF-IDF
Text keyword extractor
Find distinctive words in your document, with occurrence counts and local processing.
Local models, learning & document helpers
Choose a local model, trainable classifier or statistical helper. Inputs stay on your device; model files download only when you run a model tool.
Text & settings
Up to 64 KB · stays on your device
Analysis result
Enter your text or try a sample.
Method & limitations
Common English and Persian stop words are excluded. Remaining words are ranked using sentence-based TF-IDF and counted after normalization. No search-volume data, keyword difficulty or ranking guarantee is provided.
Runs in a Web Worker. Inputs and results are cleared when you leave or choose Clear text; they are not saved in browser storage. Downloaded files remain on your device.
A guide to this tool
How to use Text keyword extractor
- Enter your text or load this tool’s sample.
- Choose the available settings and fill in a second input if this tool has one.
- Run the analysis and review the output and method notes before using it.
A sample you can try
Sample input
An online store needs clear product information to earn customer trust. Good product photos help customers inspect the details. Compressing product photos makes store pages load faster. Website speed improves the shopping experience for customers. Product descriptions should explain materials, dimensions and how to use the item. A clear product description helps customers compare products. Customers check delivery and return policies before buying. Customer reviews can also support a purchase decision.
Sample output
1. customers — 4 occurrences 2. product — 5 occurrences 3. clear — 2 occurrences 4. customer — 2 occurrences 5. photos — 2 occurrences 6. store — 2 occurrences 7. also — 1 occurrences 8. before — 1 occurrences