Configuring Facebook chatbot text analyzer definitions

The Facebook chatbot configuration for a Pega Intelligent Virtual Assistant includes a list of text analyzer definitions. Text analyzer definitions are used for advanced text analysis to process user input and determine the best matching response. The definitions are based on natural language processing (NLP).

In the advanced configuration you can specify several text analyzer definitions to provide a better response to users. User input is analyzed by using the first text analyzer definition in the list, and if no match is found, the second text analyzer definition in the list is used, and so on, until a response match is found.

For each text analyzer definition you can also specify whether to run it within the context of a case, outside of the context of a case, or both. For example, if you have a case that allows users to buy airline tickets, you can specify to run a text analyzer definition within the context of a case so that when the chatbot asks the user about when to book the flight, the response is automatically converted to a specific date.

You must purchase a separate license before using Pega Intelligent Virtual Assistant in your application. You must also obtain and install the Facebook channel component from Pega Exchange.

You can add, delete, or modify each text analyzer definition in the list.

1. In Designer Studio, click the name of your application and click Channels and interfaces.

2. Click a Facebook channel interface.

3. Click the Behavior tab.

4. In the Text Analyzer section, click Edit categories.

   1. Click + Add category.

   2. Fill out the following fields:

      • Category - Required. The natural language processing category for the chatbot to use as the response based on its must match, approximate match, and never match criteria.
      • Must match - Optional. The comma-separated words or phrases to use as an exact match for the Facebook chat content for the category. For example, for an initial greeting response, you can specify 'hi'.
      • Approximate match - Optional. The comma-separated words or phrases to use as an approximate match for the Facebook chat content for the category. For example, for an initial greeting response, you can specify: 'hello' or 'good morning'.
      • Never match - Optional. The comma-separated words or phrases to never match for the Facebook chat content for the category. For example, for an initial greeting response, you can specify 'bye'.
   3. Repeat steps a and b to define additional categories.
   4. Click Submit.

5. Optional: Select the Use advanced configuration check box. A list of defined text analyzers is displayed.

   • To add a new text analyzer definition to the list:

     1. Click + Add text analyzer.
     2. In the Text Analyzer type list, click Exact match or Pega NLP.
     3. Optional: If you selected a Pega NLP text analyzer type, in the Text Analyzer rule field, select a text analyzer rule that contains an NLP definition to use.
     4. Optional: Select the Apply in context of a case check box to specify that the text analyzer definition is to run during a process that is specified by a case.
     5. Optional: Select the Apply outside of case context check box to specify that the text analyzer definition is to run outside of a process that is specified by case.
     6. Click Submit.

   • To modify a text analyzer in the list, click the Configuration icon.

6. Click Save.

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