You are developing the chatbot. You create the following components: * A QnA Maker resource * A chatbot by using the Azure Bot Framework SDK. You need to integrate the components to meet the chatbot requirements. Which property should you use? A. QnADialogResponseOptions.CardNoMatchText B. Qna MakerOptions-ScoreThreshold C. Qna Maker Op t ions StrickFilters D. QnaMakerOptions.RankerType do you know this answer?

Question #:4 - (Exam Topic 2)
You are developing the chatbot.
You create the following components:
• A QnA Maker resource
• A chatbot by using the Azure Bot Framework SDK
You need to add an additional component to meet the technical requirements and the chatbot requirements. What should you add?
A. Dispatch
B. chatdown
C. Language Understanding
D. Microsoft Translator
Answer: A
Explanation
Scenario: All planned projects must support English, French, and Portuguese.
If a bot uses multiple LUIS models and QnA Maker knowledge bases (knowledge bases), you can use the Dispatch tool to determine which LUIS model or QnA Maker knowledge base best matches the user input. The dispatch tool does this by creating a single LUIS app to route user input to the correct model.
Reference:
https://docs.microsoft.com/en-us/azure/bot-service/bot-builder-tutorial-dispatch
 
Question #:5 - (Exam Topic 2)
You are developing the document processing workflow.
You need to identify which API endpoints to use to extract text from the financial documents. The solution must meet the document processing requirements.
Which two API endpoints should you identify? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point.
A. /vision/v3.2/read/analyzeResults
B. /formrecognizer/v2.0/prebuilt/receipt/analyze
C. /vision/v3.2/read/analyze
D. /vision/v3.2/describe
E. /formercognizer/v2.0/custom/models{modelId}/ analyze
Answer: B C
Explanation
C: Analyze Receipt - Get Analyze Receipt Result.
Query the status and retrieve the result of an Analyze Receipt operation.
Request URL: https://{endpoint}/formrecognizer/v2.0-preview/prebuilt/receipt/analyzeResults/{resultId} E: POST {Endpoint}/vision/v3.2/read/analyze
Use this interface to get the result of a Read operation, employing the state-of-the-art Optical Character Recognition (OCR) algorithms optimized for text-heavy documents.
Scenario: Contoso plans to develop a document processing workflow to extract information automatically from PDFs and images of financial documents
The document processing solution must be able to process standardized financial documents that have the following characteristics:
- Contain fewer than 20 pages.
- Be formatted as PDF or JPEG files.
- Have a distinct standard for each office.
*The document processing solution must be able to extract tables and text from the financial documents. The document processing solution must be able to extract information from receipt images.
Reference:
https://westus2.dev.cognitive.microsoft.com/docs/services/form-recognizer-api-v2-preview/operations/GetAnaly https://docs.microsoft.com/en-us/rest/api/computervision/3.1/read/read
 
Question #:7 - (Exam Topic 2)
You are developing the chatbot.
You create the following components:
* A QnA Maker resource
* A chatbot by using the Azure Bot Framework SDK.
You need to integrate the components to meet the chatbot requirements. Which property should you use?
A. QnADialogResponseOptions.CardNoMatchText
B. Qna MakerOptions-ScoreThreshold
C. Qna Maker Op t ions StrickFilters
D. QnaMakerOptions.RankerType
Answer: D
Explanation
Scenario: When the response confidence score is low, ensure that the chatbot can provide other response options to the customers.
When no good match is found by the ranker, the confidence score of 0.0 or "None" is returned and the default response is "No good match found in the KB". You can override this default response in the bot or application code calling the endpoint. Alternately, you can also set the override response in Azure and this changes the default for all knowledge bases deployed in a particular QnA Maker service.
Choosing Ranker type: By default, QnA Maker searches through questions and answers. If you want to search through questions only, to generate an answer, use the RankerType=QuestionOnly in the POST body of the GenerateAnswer request.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/qnamaker/concepts/best-practices