You need to build a chatbot that meets the following requirements:
– Supports chit-chat, knowledge base, and multilingual models
– Performs sentiment analysis on user messages
– Selects the best language model automatically
What should you integrate into the chatbot?
A . QnA Maker, Language Understanding, and Dispatch
B . Translator, Speech, and Dispatch
C . Language Understanding, Text Analytics, and QnA Maker
D . Text Analytics, Translator, and Dispatch
Answer: C
Explanation:
Language Understanding: An AI service that allows users to interact with your applications, bots, and IoT devices by using natural language.
QnA Maker is a cloud-based Natural Language Processing (NLP) service that allows you to create a natural conversational layer over your data. It is used to find the most appropriate answer for any input from your custom knowledge base (KB) of information.
Text Analytics: Mine insights in unstructured text using natural language processing (NLP)―no machine learning expertise required. Gain a deeper understanding of customer opinions with sentiment analysis. The Language Detection feature of the Azure Text Analytics REST API evaluates text input
Incorrect Answers:
A, B, D: Dispatch uses sample utterances for each of your bot’s different tasks (LUIS, QnA Maker, or custom), and builds a model that can be used to properly route your user’s request to the right task, even across multiple bots.
Reference:
https://azure.microsoft.com/en-us/services/cognitive-services/text-analytics/
https://docs.microsoft.com/en-us/azure/cognitive-services/qnamaker/overview/overview
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