Cognitive computing: theory and applications / [edited by] Venkat N. Gudivada...[et al.].

Includes bibliographical references and index.

Section A: Fundamentals and Principles --
Chapter 1: Cognitive Computing: Concepts, Architectures, Systems, and Applications --
Chapter 2: Cognitive Computing and Neural Networks: Reverse Engineering the Brain --
Section B: Complex Analytics and Machine Learning --
Chapter 3: Visual Analytic Decision-Making Environments for Large-Scale Time-Evolving Graphs --
Chapter 4: CyGraph: Graph-Based Analytics and Visualization for Cybersecurity --
Chapter 5: Cognitive Analytics: Going Beyond Big Data Analytics and Machine Learning --
Chapter 6: A Cognitive Random Forest: An Intra- and Intercognitive Computing for Big Data Classification Under Cune Condition --
Chapter 7: Bayesian Additive Regression Tree for Seemingly Unrelated Regression with Automatic Tree Selection --
Section C: Applications --
Chapter 8: Cognitive Systems for the Food-Water-Energy Nexus --
Chapter 9: Cognitive Computing Applications in Education and Learning --
Chapter 10: Large-Scale Data Enabled Evolution of Spoken Language Research and Applications --
Chapter 11: The Internet of Things and Cognitive Computing.

Cognitive Computing: Theory and Applications, written by internationally renowned experts, focuses on cognitive computing and its theory and applications, including the use of cognitive computing to manage renewable energy, the environment, and other scarce resources, machine learning models and algorithms, biometrics, Kernel Based Models for transductive learning, neural networks, graph analytics in cyber security, neural networks, data driven speech recognition, and analytical platforms to study the brain-computer interface.