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Defining topics for text analysis for an email bot

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Define topics in Pega Email Bot so that the system determines the best response by analyzing an email through natural language processing (NLP) and adaptive analytics text analysis models. Defined topics help the email bot detect and organize suggested responses and suggested cases in the system.

You can configure multiple languages for the email bot by setting up text analysis for each language separately. This ensures that the system performs text analysis of email in the correct language that is detected. For more information, see Selecting languages for an Email channel.

All suggested cases that you define in the system are topics.
  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. In the Email channel, click the Behavior tab.

  4. Optional:

    To enable the advanced configuration mode, in the Text Analyzer section, select the Use advanced configuration check box.

    In the advanced configuration mode, you configure the advanced text analyzers in the system that use NLP and adaptive analytics. If you do not use advanced configuration, you configure the default text analyzer that exactly matches user input to a response. For more information, see Exploring text analyzers .

  5. In the Text Analyzer section, click Edit topics for the text analyzer that you want to edit.

  6. In the Edit topics window, click Add topic.

    A topic is the general subject, the intent of an email that the system detects using text analysis.

  7. If you configure multiple languages for the email bot, in the section in the Edit topics window, click a language.

    The supported languages are displayed on a vertical tab. When you add a new topic or edit an existing topic, you can switch between the languages by clicking the name of a language.

  8. In the table columns, specify a topic and matching criteria:

    • In the Topic field, enter the natural language processing topic for the email bot to use as the response. The NLP text analyzer determines the topic based on criteria that matches exactly, matches approximately, and or never matches the user input.
    • In the Approximate match field, to configure the email bot to look for approximate matches in the user input, enter words and phrases that you want to use, and then separate them with commas. For example, for an initial greeting responses, enter: hello, good morning.
    • In the Must match field, to configure the email bot to look for specific items in the email, enter words and phrases that you want to exactly match in the topic, and separate them with commas. For example, for initial greeting response, enter hi.
    • In the Never match field, enter comma-separated words or phrases to always ignore when matching for the topic. For example, for an initial greeting response to never match a goodbye greeting, enter bye.
  9. Optional:

    To configure additional languages for the topic, repeat steps 7 through 8.

  10. Optional:

    To add more topics for text analysis, repeat steps 6 through 9.

  11. Click Submit.

  12. Click Save.

The email bot uses text analysis to match content in the email body or attachments to a topic, a suggested case or a suggested response.

  • 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.

  • Configuring email analysis

    Improve automatic actions that the system performs on emails, by configuring Pega Email Bot that analyzes email content for topics, sentiment, language, and entities. You can also configure additional analysis for the email subject field and file attachments.

  • Defining Email channel behavior

    Configure how the Email channel automatically responds to email requests, so that you can route email content and create top-level cases in your application. To ensure that the responses are meaningful and contextual, you can define such parameters as suggested cases and responses, and configure email analysis of the subject field and file attachments.


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