Table of Contents

Enabling the training data recording for an email bot


Only available versions of this content are shown in the dropdown

To train Pega Email Bot to make better email content predictions, enable the recording of training data in the system. You can then edit and classify the training data in the system by reviewing records and applying changes to the text analytics model. With these tasks, you ensure that the email bot detects the correct topics and entities.

Build an email bot by configuring the Email channel. For more information, see Building an Email channel.
  1. In the header of Dev Studio, click the name of the application, and then click Channels and interfaces.

  2. In the Current channel interfaces section, click the icon that represents your existing Email channel.

  3. On the Email channel configuration page, click the Behavior tab.

  4. In the Text Analyzer section, activate the recording of training data:

    Choices Action
    For the default text analyzer
    1. Select the Record training data check box.

    For an advanced configuration
    1. In the text analyzer list, click the Switch to edit mode icon for a text analyzer.

    2. In the Text analyzer configuration window, select the Enable model training check box.

    3. Click Submit.

  5. Click Save.

Improve the text analytics model by manually creating data records for the email bot. For more information, see Creating training data manually for an email bot.

  • Understanding text analysis

    Text analysis is an important aspect of conversational channels that enables a Pega Platform application to intelligently and seamlessly interact with a user in a natural conversational manner. Text analyzers examine user input one by one using natural language processing (NLP), adaptive analytics, and artificial intelligence.

  • Exploring text analyzers

    Text analyzers for Pega Intelligent Virtual Assistant (IVA) and Pega Email Bot process user input and help the system find the best matching response by using natural language processing (NLP) and adaptive analytics. You can configure text analyzers to detect topics, entities, sentiment, and language in an email, chat text message, or a voice command.

  • Training data for the Email channel

    To use Pega Email Bot in your application to seamlessly respond to user problems, train the system to recognize different user input in emails, such as help requests or issues. When you train the data for the email bot, the system learns from training records, improves the artificial intelligence algorithms, and provides better responses to user input.

0% found this useful

Have a question? Get answers now.

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