Learn which Azure cognitive service enables a chatbot to answer user questions based on information from PDF, Word, and web documents. Discover how QnA Maker can ingest and process unstructured data to build a knowledge base for your conversational AI application.
Table of Contents
Question
You are developing a chatbot for a website, and need to implement a requirement that the chatbot must answer user’s questions based on the information in the following documents:
- A frequently asked questions (FAQ) list on a PDF file
- A product troubleshooting guide in a Microsoft Word document
- A frequently asked questions (FAQ) list on a webpage
Which service should you use to process the documents?
A. QnA Maker
B. Azure Bot Service
C. Text Analytics
D. Language Understanding
Answer
A. QnA Maker
Explanation
QnA Maker is an Azure cognitive service that allows you to create a knowledge base of question-and-answer pairs from semi-structured content like FAQ documents, product manuals, and web pages. It uses natural language processing (NLP) to extract relevant question-answer pairs from your documents.
Key features of QnA Maker:
- Ingests unstructured and semi-structured data in various formats like PDF, Microsoft Word, and web pages
- Automatically extracts question-answer pairs to build a knowledge base
- Supports contextual follow-up prompts to refine the user’s original query
- Integrates with the Azure Bot Service to build a conversational interface
- Includes a built-in natural language processing model to interpret user queries
The other options are incorrect because:
- Azure Bot Service provides the framework to build and deploy chatbots, but does not directly process documents to extract Q&A pairs. It integrates with QnA Maker and other services.
- Text Analytics is used for sentiment analysis, key phrase extraction, named entity recognition, and language detection on unstructured text. It does not build a Q&A knowledge base.
- Language Understanding (LUIS) is used to build natural language understanding models that identify user intents and entities. It is not designed for extracting question-answer pairs from documents.
In summary, QnA Maker is the best choice to process the FAQ PDF, product troubleshooting guide in Word, and FAQ web page in order to build a knowledge base that the chatbot can use to answer user questions. Its ability to ingest unstructured data in various formats and automatically extract relevant Q&A pairs makes it ideally suited for this requirement.
To implement a chatbot that answers user questions based on information from various documents, you should use: QnA Maker – This service is designed to create a question-and-answer knowledge base from documents such as FAQs and troubleshooting guides. It allows you to upload and process documents to build a knowledge base that the chatbot can query to provide relevant answers. So the correct answer is QnA Maker.
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