Microsoft Azure AI Fundamentals Natural Language Processing(3).pdf

# Introduction - 1 minute We are used to being able to communicate at any time of the day or night, anywhere in the world, putting organizations under pressure to react fast enough to their customers. We want personal responses to our queries, without having to read in-depth documentation to find...

# Introduction - 1 minute We are used to being able to communicate at any time of the day or night, anywhere in the world, putting organizations under pressure to react fast enough to their customers. We want personal responses to our queries, without having to read in-depth documentation to find answers. This often means that support staff get overloaded with requests for help through multiple channels, and that people are left waiting for a response. Conversational AI describes solutions that enable a dialog between an AI agent and a human. Generically, conversational AI agents are known as bots. People can engage with bots through channels such as web chat interfaces, email, social media platforms, and more. Azure AI Language's question answering feature provides you with the ability to create conversational AI solutions. Next you'll learn about question answering. # Understand question answering - 2 minutes Question answering supports natural language AI workloads that require an automated conversational element. Typically, question answering is used to build bot applications that respond to customer queries. Question answering capabilities can respond immediately, answer concerns accurately, and interact with users in a natural multi-turned way. Bots can be implemented on a range of platforms, such as a web site or a social media platform. Question answering applications provide a friendly way for people to get answers to their questions and allows people to deal with queries at a time that suits them, rather than during office hours. In the following example, a chat bot uses natural language and provides options to a customer to best handle their query. The user gets an answer to their question quickly, and only gets passed to a person if their query is more complicated. # Get started with custom question answering - 3 minutes You can easily create a question answering solution on Microsoft Azure using Azure AI Language service. Azure AI Language includes a custom question answering feature that enables you to create a knowledge base of question and answer pairs that can be queried using natural language input. # Creating a custom question answering knowledge base - You can use Azure AI Language Studio to create, train, publish, and manage question answering projects. - **Note:** You can write code to create and manage projects using the Azure AI Language REST API or SDK. However, in most scenarios it is easier to use the Language Studio. To create a project, you must first provision a Language resource in your Azure subscription. - **Define questions and answers** After provisioning a Language resource, you can use the Language Studio's custom question answering feature to create a project that consists of question-and-answer pairs. These questions and answers can be: - Generated from an existing FAQ document or web page. - Entered and edited manually. In many cases, a project is created using a combination of all of these techniques; starting with a base dataset of questions and answers from an existing FAQ document and extending the knowledge base with additional manual entries. Questions in the project can be assigned alternative phrasing to help consolidate questions with the same meaning. For example, you might include a question like: - What is your head office location? You can anticipate different ways this question could be asked by adding an alternative phrasing such as: - Where is your head office located? - **Test the project** After creating a set of question-and-answer pairs, you must save it. This process analyzes your literal questions and answers and applies a built-in natural language processing model to match appropriate answers to questions, even when they are not phrased exactly as specified in your question definitions. Then you can use the built-in test interface in the Language Studio to test your knowledge base by submitting questions and reviewing the answers that are returned. # Knowledge Check - 2 minutes - 1. Your organization has an existing frequently asked questions (FAQ) document. You need to create a knowledge base that includes the questions and answers from the FAQ with the least possible effort. What should you do? - Import the existing FAQ document into a new knowledge base. - 2. You want to create a knowledge base for your organization's bot service. Which Azure AI service is best suited to creating a knowledge base? - Question Answering - 3. You have published your conversational language understanding application. What information does a client application developer need to get predictions from it? - The endpoint and key for the application's prediction resource # Summary - 1 minute Azure AI Language's custom question answering feature enables you to define and publish a knowledge base of questions and answers with support for natural language querying. The ability to create conversational AI solutions with Azure AI Language's custom question answering feature makes it possible for AI agents to reduce the support workload for human personnel; enabling organizations to provide user support at global scale.