Three Ways to Create QnA Maker Content
Question
You need to provide content for a business chatbot that will help answer simple user queries.
What are three ways to create question and answer text by using QnA Maker? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
Answers
Explanations
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A. B. C. D. E.ACE
Automatic extraction -
Extract question-answer pairs from semi-structured content, including FAQ pages, support websites, excel files, SharePoint documents, product manuals and policies.
https://docs.microsoft.com/en-us/azure/cognitive-services/qnamaker/concepts/content-typesQnA Maker is a cloud-based natural language processing (NLP) tool provided by Microsoft Azure that can be used to create a knowledge base of questions and answers for chatbots, virtual assistants, and other conversational AI applications. QnA Maker enables developers and content creators to easily and quickly create, train, and publish a chatbot that can answer common user queries.
The three ways to create question and answer text using QnA Maker are:
A. Generate the questions and answers from an existing webpage: QnA Maker can generate questions and answers from an existing webpage by using its built-in web page scraping capability. This feature allows developers to extract questions and answers from a website's frequently asked questions (FAQ) page and use them to create a knowledge base for the chatbot. QnA Maker also allows users to customize the generated questions and answers to improve their accuracy.
B. Use automated machine learning to train a model based on a file that contains the questions: QnA Maker can also use automated machine learning (AutoML) to train a model based on a file that contains the questions and answers. This method involves providing QnA Maker with a file that contains the questions and their corresponding answers, and then using AutoML to automatically generate a knowledge base that can be used to power the chatbot. AutoML uses machine learning algorithms to analyze the questions and answers in the file and identify patterns that can be used to improve the accuracy of the chatbot's responses.
C. Manually enter the questions and answers: The third way to create question and answer text using QnA Maker is to manually enter the questions and answers into the knowledge base. This method involves creating a new knowledge base in QnA Maker and then manually adding the questions and their corresponding answers. This method is useful when there is no existing source of questions and answers or when the questions and answers need to be customized for the specific use case.
D. Connect the bot to the Cortana channel and ask questions by using Cortana: This option is not correct as it is not related to creating the questions and answers in QnA Maker. Instead, it is a feature of Cortana, Microsoft's virtual assistant, which allows users to interact with their chatbot by asking questions through Cortana.
E. Import chit-chat content from a predefined data source: This option is also not correct as it is not related to creating a knowledge base of questions and answers. Importing chit-chat content is useful for adding personality and engaging users in non-functional conversations, but it is not a way to create a knowledge base for answering user queries.
In conclusion, the three ways to create question and answer text using QnA Maker are to generate the questions and answers from an existing webpage, use automated machine learning to train a model based on a file that contains the questions, and manually enter the questions and answers into the knowledge base.
