Table of Contents

Defining topics for text analysis for an IVA


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Define topics in Pega Intelligent Virtual Assistant (IVA) so that the system determines the best response by analyzing user input through natural language processing (NLP) and adaptive analytics text analysis models. Topics help the IVA detect and organize suggested responses and suggested cases in the system.

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 Unified Messaging, Web Chatbot, or Alexa channel.

  3. In the channel, click the Behavior tab.

  4. 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 a voice command or a text message that the system detects using text analysis.

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

    • In the Topic field, enter the natural language processing topic for the IVA to use as the response. The NLP text analyzer determines the topic based on criteria that either matches exactly, matches approximately, and or never matches the user input.
    • In the Approximate match field, to configure the IVA 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 IVA to look for specific items in the conversation content, enter words and phrases that you want to exactly match in the topic, and separate them with commas. For example, for an 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.
  8. Optional:

    To add more topics to a text analyzer, repeat step 6 and 7.

  9. Click Submit.

  10. Click Save.

The IVA uses text analysis to match user input to a topic, a case command, or a response command.

  • 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 text analyzer settings

    Improve the way Pega Intelligent Virtual Assistant (IVA) responds to user input by configuring text analyzers. The IVA uses natural language processing (NLP) and adaptive analytics text analyzers to detect entities, topics, sentiment, and language in the interaction with the user.

  • Defining conversational channel behavior

    Improve user experience in Pega Intelligent Virtual Assistant (IVA) by configuring the conversational channel behavior that fit the needs of your organization. You can add a conversation to a case type, add suggested cases, and define suggested responses for the IVA so that you speed up business processes for a Pega Platform application.

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