Skip to main content


         This documentation site is for previous versions. Visit our new documentation site for current releases.      
 

Setting up a keyword-based topic detection model

Updated on July 5, 2022

Create a keyword-based topic detection model by specifying the model name, language, and corresponding ruleset. After you create the model, complete the model configuration by defining a taxonomy of topics and keywords.

  1. In the navigation pane of Prediction Studio, click Models.
  2. In the header of the Models work area, click NewText categorization.
  3. In the New text categorization model window, perform the following actions:
    1. In the Name field, enter a name for the topic detection model.
    2. In the Language list, select a language for the model to use.
      For more information, see Language support for NLP.
    3. In the What do you want to detect? section, click Topics, and then select the Use category keywords check box.
    4. In the Save taxonomy section, specify the class in which you want to save the model, and then specify its ruleset or branch.
    5. Click Create.
What to do next: Complete the model configuration in one of the following ways:
  • Previous topic Creating keyword-based topic detection models
  • Next topic Creating a taxonomy for keyword-based topic detection

Have a question? Get answers now.

Visit the Support Center to ask questions, engage in discussions, share ideas, and help others.

Did you find this content helpful?

Want to help us improve this content?

We'd prefer it if you saw us at our best.

Pega.com is not optimized for Internet Explorer. For the optimal experience, please use:

Close Deprecation Notice
Contact us