Cognitive Computing and Big Data Analytics

Cognitive Computing and Big Data Analytics

by Judith S. Hurwitz, Marcia Kaufman, Adrian Bowles
Released March 2015
Publisher(s): Wiley
ISBN: 9781118896624

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Book description

A comprehensive guide to learning technologies that unlock the value in big data

Cognitive Computing provides detailed guidance toward building a new class of systems that learn from experience and derive insights to unlock the value of big data. This book helps technologists understand cognitive computing's underlying technologies, from knowledge representation techniques and natural language processing algorithms to dynamic learning approaches based on accumulated evidence, rather than reprogramming. Detailed case examples from the financial, healthcare, and manufacturing walk readers step-by-step through the design and testing of cognitive systems, and expert perspectives from organizations such as Cleveland Clinic, Memorial Sloan-Kettering, as well as commercial vendors that are creating solutions. These organizations provide insight into the real-world implementation of cognitive computing systems. The IBM Watson cognitive computing platform is described in a detailed chapter because of its significance in helping to define this emerging market. In addition, the book includes implementations of emerging projects from Qualcomm, Hitachi, Google and Amazon.

Today's cognitive computing solutions build on established concepts from artificial intelligence, natural language processing, ontologies, and leverage advances in big data management and analytics. They foreshadow an intelligent infrastructure that enables a new generation of customer and context-aware smart applications in all industries.

Cognitive Computing is a comprehensive guide to the subject, providing both the theoretical and practical guidance technologists need.

  • Discover how cognitive computing evolved from promise to reality
  • Learn the elements that make up a cognitive computing system
  • Understand the groundbreaking hardware and software technologies behind cognitive computing
  • Learn to evaluate your own application portfolio to find the best candidates for pilot projects
  • Leverage cognitive computing capabilities to transform the organization

Cognitive systems are rightly being hailed as the new era of computing. Learn how these technologies enable emerging firms to compete with entrenched giants, and forward-thinking established firms to disrupt their industries. Professionals who currently work with big data and analytics will see how cognitive computing builds on their foundation, and creates new opportunities. Cognitive Computing provides complete guidance to this new level of human-machine interaction.

Table of contents

  1. Introduction
    1. Human Intelligence + Machine Intelligence
    2. Putting the Pieces Together
    3. The Book’s Focus
    4. Overview of the Book and Technology
    5. How This Book Is Organized
  2. Chapter 1 The Foundation of Cognitive Computing
    1. Cognitive Computing as a New Generation
    2. The Uses of Cognitive Systems
    3. What Makes a System Cognitive?
    4. Gaining Insights from Data
    5. Artificial Intelligence as the Foundation of Cognitive Computing
    6. Understanding Cognition
    7. Two Systems of Judgment and Choice
    8. Understanding Complex Relationships Between Systems
    9. The Elements of a Cognitive System
    10. Summary
  3. Chapter 2 Design Principles for Cognitive Systems
    1. Components of a Cognitive System
    2. Building the Corpus
    3. Bringing Data into the Cognitive System
    4. Machine Learning
    5. Hypotheses Generation and Scoring
    6. Presentation and Visualization Services
    7. Summary
  4. Chapter 3 Natural Language Processing in Support of a Cognitive System
    1. The Role of NLP in a Cognitive System
    2. Semantic Web
    3. Applying Natural Language Technologies to Business Problems
    4. Summary
  5. Chapter 4 The Relationship Between Big Data and Cognitive Computing
    1. Dealing with Human-Generated Data
    2. Defining Big Data
    3. The Architectural Foundation for Big Data
    4. Analytical Data Warehouses
    5. Hadoop
    6. Data in Motion and Streaming Data
    7. Integration of Big Data with Traditional Data
    8. Summary
  6. Chapter 5 Representing Knowledge in Taxonomies and Ontologies
    1. Representing Knowledge
    2. Defining Taxonomies and Ontologies
    3. Explaining How to Represent Knowledge
    4. Models for Knowledge Representation
    5. Implementation Considerations
    6. Summary
  7. Chapter 6 Applying Advanced Analytics to Cognitive Computing
    1. Advanced Analytics Is on a Path to Cognitive Computing
    2. Key Capabilities in Advanced Analytics
    3. Using Advanced Analytics to Create Value
    4. Impact of Open Source Tools on Advanced Analytics
    5. Summary
  8. Chapter 7 The Role of Cloud and Distributed Computing in Cognitive Computing
    1. Leveraging Distributed Computing for Shared Resources
    2. Why Cloud Services Are Fundamental to Cognitive Computing Systems
    3. Characteristics of Cloud Computing
    4. Cloud Computing Models
    5. Delivery Models of the Cloud
    6. Managing Workloads
    7. Security and Governance
    8. Data Integration and Management in the Cloud
    9. Summary
  9. Chapter 8 The Business Implications of Cognitive Computing
    1. Preparing for Change
    2. Advantages of New Disruptive Models
    3. What Does Knowledge Mean to the Business?
    4. The Difference with a Cognitive Systems Approach
    5. Meshing Data Together Differently
    6. Using Business Knowledge to Plan for the Future
    7. Answering Business Questions in New Ways
    8. Building Business Specific Solutions
    9. Making Cognitive Computing a Reality
    10. How a Cognitive Application Can Change a Market
    11. Summary
  10. Chapter 9 IBM’s Watson as a Cognitive System
    1. Watson Defined
    2. Advancing Research with a “Grand Challenge”
    3. Preparing Watson for Jeopardy!
    4. Preparing Watson for Commercial Applications
    5. The Components of DeepQA Architecture
    6. Summary
  11. Chapter 10 The Process of Building a Cognitive Application
    1. The Emerging Cognitive Platform
    2. Defining the Objective
    3. Defining the Domain
    4. Understanding the Intended Users and Defining their Attributes
    5. Defining Questions and Exploring Insights
    6. Creating and Refining the Corpora
    7. Training and Testing
    8. Summary
  12. Chapter 11 Building a Cognitive Healthcare Application
    1. Foundations of Cognitive Computing for Healthcare
    2. Constituents in the Healthcare Ecosystem
    3. Learning from Patterns in Healthcare Data
    4. Building on a Foundation of Big Data Analytics
    5. Cognitive Applications across the Healthcare Ecosystem
    6. Starting with a Cognitive Application for Healthcare
    7. Using Cognitive Applications to Improve Health and Wellness
    8. Using a Cognitive Application to Enhance the Electronic Medical Record
    9. Using a Cognitive Application to Improve Clinical Teaching
    10. Summary
  13. Chapter 12 Smarter Cities: Cognitive Computing in Government
    1. How Cities Have Operated
    2. The Characteristics of a Smart City
    3. The Rise of the Open Data Movement Will Fuel Cognitive Cities
    4. The Internet of Everything and Smarter Cities
    5. Understanding the Ownership and Value of Data
    6. Cities Are Adopting Smarter Technology Today for Major Functions
    7. Smarter Approaches to Preventative Healthcare
    8. Building a Smarter Transportation Infrastructure
    9. Using Analytics to Close the Workforce Skills Gap
    10. Creating a Cognitive Community Infrastructure
    11. The Next Phase of Cognitive Cities
    12. Summary
  14. Chapter 13 Emerging Cognitive Computing Areas
    1. Characteristics of Ideal Markets for Cognitive Computing
    2. Vertical Markets and Industries
    3. Summary
  15. Chapter 14 Future Applications for Cognitive Computing
    1. Requirements for the Next Generation
    2. Technical Advancements That Will Change the Future of Cognitive Computing
    3. What the Future Will Look Like
    4. Emerging Innovations
    5. Summary
  16. Glossary
  17. Title page
  18. Copyright
  19. Dedication
  20. About the Technical Editors
  21. About the Authors
  22. Acknowledgments
  23. EULA

Product information

  • Title: Cognitive Computing and Big Data Analytics
  • Author(s): Judith S. Hurwitz, Marcia Kaufman, Adrian Bowles
  • Release date: March 2015
  • Publisher(s): Wiley
  • ISBN: 9781118896624