Book Image

Learning Microsoft Cognitive Services - Second Edition

By : Leif Larsen
Book Image

Learning Microsoft Cognitive Services - Second Edition

By: Leif Larsen

Overview of this book

Microsoft has revamped its Project Oxford to launch the all new Cognitive Services platform-a set of 30 APIs to add speech, vision, language, and knowledge capabilities to apps. This book will introduce you to 24 of the APIs released as part of Cognitive Services platform and show you how to leverage their capabilities. More importantly, you'll see how the power of these APIs can be combined to build real-world apps that have cognitive capabilities. The book is split into three sections: computer vision, speech recognition and language processing, and knowledge and search. You will be taken through the vision APIs at first as this is very visual, and not too complex. The next part revolves around speech and language, which are somewhat connected. The last part is about adding real-world intelligence to apps by connecting them to Knowledge and Search APIs. By the end of this book, you will be in a position to understand what Microsoft Cognitive Service can offer and how to use the different APIs.
Table of Contents (19 chapters)
Title Page
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface

Chapter 8. Querying Structured Data in a Natural Way

In the previous chapter, we learned how we could use the current context to extend our knowledge on a certain topic. Throughout this chapter, we will continue with the Knowledge APIs. More specifically, we will learn how to explore relationships between academic papers and journals. We will see how we can interpret natural language queries, and get query expressions. Using these expressions, we will learn how to find academic entities. The next part will focus more on how to set up this kind of service on your own. At the end, we will look into the QnA Maker, to see how we can create FAQ services from existing content.

When we have completed this chapter, we will have covered the following topics:

  • Interpreting natural language user queries using the Academic API
  • Assisting the user with queries, using autocomplete features
  • Using said queries to retrieve academic entities
  • Calculating the distribution of academic entities from the queries
  • Hosting...