Building Cognitive Applications with IBM Watson Services: Volume 4 Natural Language Classifier

A draft IBM Redbooks publication

Updated 01 May 2017

cover image

ISBN-10: 0738442593
ISBN-13: 9780738442594
IBM Form #: SG24-8391-00
(142 pages)

Authors: Marcelo Mota Manhaes, Taemin Ko, Abeer Selim, Omar Amer, Lak Sri

Abstract

The Building Cognitive Applications with IBM Watson Services series is a seven-volume collection that introduces IBM® Watson cognitive computing services. The series includes an overview of specific Watson services with their associated architectures and simple code examples. Each volume describes how you can use and implement these services in your applications through practical use cases.

The series includes the following volumes:


  • Volume 1 Getting Started, SG24-8387
  • Volume 2 Conversation, SG24-8394
  • Volume 3 Visual Recognition, SG24-8393
  • Volume 4 Natural Language Classifier, SG24-8391
  • Volume 5 Language Translator, SG24-8392
  • Volume 6 Speech to Text and Text to Speech, SG24-8388
  • Volume 7 Natural Language Understanding, SG24-8398


Whether you are a beginner or an experienced developer, this collection provides the information you need to start your research on Watson services. If your goal is to become more familiar with Watson in relation to your current environment, or if you are evaluating cognitive computing, this collection can serve as a powerful learning tool.

This IBM Redbooks® publication, Volume 4, introduces the Watson Natural Language Classifier service. This service applies cognitive computing techniques to return best matching predefined classes for short text inputs such as a sentence or phrase. The book describes concepts that you need to understand to create, use and train the classifier. This book describes how to prepare training data, and create and train the classifier to connect the classes to example texts so the service can apply the classes to new inputs. It provides examples of applications that demonstrate how to use the Watson Natural Language Classifier service in practical use cases. You can develop and deploy the sample applications by following along in a step-by-step approach and using provided code snippets. Alternatively, you can download an existing Git project to more quickly deploy the application.

Table of contents

Chapter 1. Basics of Natural Language Classifier API
Chapter 2. Creating a Natural Language Classifier service in Bluemix
Chapter 3. Healthcare Questions and Answers
Chapter 4. News Classification
Chapter 5. SPAM Classifier
Appendix A. Additional material

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