Explanation Based Learning

A type of machine learning known as explanation-based learning, or EBL for short, takes advantage of an extremely robust, or even flawless, domain theory in order to generalize from training data or construct concepts. It also has a connection with encoding, or memory, which assists with learning.

How You Will Benefit

(I) Insights, and validations about the following topics:

Chapter 1: Explanation-based learning

Chapter 2: Computational linguistics

Chapter 3: Natural language processing

Chapter 4: Corpus linguistics

Chapter 5: Parsing

Chapter 6: Question answering

Chapter 7: Link grammar

Chapter 8: Grammar induction

Chapter 9: Structured prediction

Chapter 10: Deep linguistic processing

(II) Answering the public top questions about explanation based learning.

(III) Real world examples for the usage of explanation based learning in many fields.

(IV) 17 appendices to explain, briefly, 266 emerging technologies in each industry to have 360-degree full understanding of explanation based learning' technologies.

Who This Book Is For

Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of explanation based learning.