Adding a text analyzer for an IVA

To provide better responses by Pega Intelligent Virtual Assistant (IVA), you can configure one or more advanced text analyzers together for an application. In that case, the text analyzers examine user input one by one, until the system finds a response.

You can also configure one text analyzer to run only within the case context, and another one to run outside of the case context. For example, to refine interaction with a user once a case is started in the IVA, you can specify the iNLP advanced text analyzer to improve the text analysis of user input, while using the simple exact match text analyzer when a case is not started during a chat session.

Note: The system uses natural language processing (NLP) and adaptive analytics text analysis to detect topics and entities in the interaction conversation.
  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 for your existing Alexa, Unified Messaging, or Web Chatbot channel.
  3. In the channel, click the Behavior tab.
  4. In the Text Analyzer section, select the Use advanced configuration check box.
  5. In the Text Analyzer section, select a method for configuring a text analyzer:
    • To create a text analyzer, click Add text analyzer.
    • To edit an existing text analyzer, click the Switch to edit mode icon next to the text analyzer that you want to edit.
  6. In the Text analyzer type list, select and configure a text analyzer:
    Choices Actions
    Exact match Configure the default text analyzer that exactly matches user input to a response:
    1. Select whether to use text analyzer within the case context, outside of the case context, or both.
    2. Click Submit.
    Pega NLP Configure an advanced text analyzer that uses the best approximate match by using advanced natural language processing (NLP) and artificial intelligence:
    1. Select or define a text analyzer rule for this definition type with the sentiment, classification, topic, and entity extraction analysis.
    2. Select whether you want to detect entities or topics within the case context, outside of the case context, or both.
    3. In the Text analyzer rule field, create or select a text analyzer rule.
    4. Click Submit.
    iNLP Configure an advanced intelligent NLP text analyzer that uses adaptive analytics text analysis:
    1. Select whether you want to detect entities or topics within the case context, outside of the case context, or both.
    2. In the Text analyzer rule field, create or select a text analyzer rule.
    3. Click Submit.

    This type of analysis integrates text analytics with strategies, propositions, and interaction history to provide the context for making better next-best-action decisions. For more information, see the Pega Community Customizable Interaction API for text analytics article.

    Dialogflow Configure an external NLP and entity extraction solution from Google:
    1. Select whether you want to detect entities or topics within the case context, outside of the case context, or both.
    2. In the Dialogflow client access token field, enter the client access token API key for the Dialogflow agent.
    3. In the Dialogflow developer access token field, enter the developer access token API key for the Dialogflow agent.
    4. Click Submit.
    Note: If you want to configure the Dialogflow text analyzer, obtain and install the Dialogflow text analyzer component from Pega Marketplace. For more information, see Installing the Dialogflow component
  7. Optional: To add or configure more text analyzers for the IVA, repeat steps 5 and 6.
  8. Click Save.
What to do next: Define the topics for text analysis in the IVA. For more information, see Defining topics for text analysis for an IVA.