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Index
Cover image
Title page
Table of Contents
Copyright
Contributors
Preface
Audience
Organization
Part A: Linguistic Principles and Computational Resources
Chapter 1: Linguistics: Core Concepts and Principles
Abstract
1 Introduction
2 Subfields of Linguistics
3 Variation in Languages
4 Phonetics
5 Phonology
6 Morphology
7 Syntax
8 Semantics
9 Summary
Acknowledgment
Chapter 2: Languages and Grammar
Abstract
1 Introduction
2 Formal Grammars
3 Grammar Classes and Corresponding Languages
4 A Simplistic Context-free Grammar for English Language
5 Summary
Chapter 3: Open-Source Libraries, Application Frameworks, and Workflow Systems for NLP
Abstract
1 Introduction
2 Corpus Datasets
3 NLP Datasets
4 Treebanks
5 Software Libraries and Frameworks for Machine Learning
6 Software Libraries and Frameworks for NLP
7 Task-Specific NLP Tools
8 Workflow Systems
9 Conclusions
Acknowledgment
Part B: Mathematical and Machine Learning Foundations
Chapter 4: Mathematical Essentials
Abstract
1 Introduction
2 Functions
3 Linear Algebra
4 Information Theory
5 Optimization
Chapter 5: Probability Essentials
Abstract
1 Preliminaries
2 Formal Definitions
3 Conditional Probability
4 Bayes Theorem
5 ℝ-Valued Random Variables
6 ℝn-Valued Random Variables
7 Independent Random Variables
8 Central Limit Theorem
Chapter 6: Inference and Prediction
Abstract
1 Introduction
2 Notation
3 Sufficient Statistics
4 Likelihood Principle
5 Point Estimation
6 Hypothesis Testing
7 Interval Estimation
8 Bayesian Methods
9 Prediction and Model Selection
Chapter 7: Bayesian Methods
Abstract
1 Bayesian Methods
2 Bayesian Networks
3 Conceptual Exercises
4 Markov Networks
5 Inference in Markov Networks
6 Conceptual Exercises
7 Summary
Acknowledgments
Chapter 8: Machine Learning
Abstract
1 Introduction to Machine Learning
2 Terminologies
3 Regularization and Bias–Variance Trade-Off
4 Evaluating Machine Learning Algorithms
5 Regression Algorithms
6 Classification Algorithms
7 Clustering Algorithms
8 Applications
9 Conclusion
Chapter 9: Deep Neural Networks for Natural Language Processing
Abstract
1 Introduction
2 Word Vectors Representations
3 Feedforward Neural Networks
4 Training Deep Models and Optimization
5 Regularization for Deep Learning
6 Sequence Modeling (Language Modeling)
7 Convolutional Neural Networks
8 Memory
9 Summary
Chapter 10: Deep Learning for Natural Language Processing
Abstract
1 Introduction
2 Survey of Deep Learning Techniques on NLP
3 Sentence Embedding Based on SOM
4 Representing, Visualizing, and Processing Documents as Images
5 Discussion and Conclusion
Part C: Applications and Linguistic Diversity
Chapter 11: Information Retrieval: Concepts, Models, and Systems
Abstract
1 Introduction
2 A Reference Architecture for Current IR Systems
3 Document Preprocessing
4 Mini Gutenberg Text Corpus
5 A Categorization of IR Models
6 Boolean IR Model
7 Positional Index, Phrase, and Proximity Queries
8 Term Weighting
9 Vector Space IR Model
10 Probabilistic IR Models
11 Language Model-Based IR
12 Evaluating IR Systems
13 Relevance Feedback and Query Expansion
14 IR Libraries, Frameworks, and Test Collections
15 Facets of IR Research
16 Additional Reading
Acknowledgments
Chapter 12: Natural Language Core Tasks and Applications
Abstract
1 Introduction
2 Annotated Language Corpora
3 Language Identification
4 Text and Word Segmentation
5 Word-Sense Disambiguation (WSD)
6 Language Modeling
7 PoS Tagging
8 Parsing
9 Named Entity Recognition
10 Machine Translation
11 Information Extraction
12 Text Summarization
13 Question-Answering Systems
14 Natural Language User Interfaces
15 Summary
Acknowledgments
Chapter 13: Linguistic Elegance of the Languages of South India
Abstract
1 Introduction
2 History and Evolution of Dravidian Languages
3 Linguistic Elegance and Language Traditions of South Indian Languages
4 Classical Languages of India
5 Influence of Other Languages on South Indian Languages
6 Summary
Chapter 14: Text Mining for Modeling Cyberattacks
Abstract
1 Introduction
2 Anatomy of an Attack Pattern
3 Applying Attack Patterns to Scenarios
4 Mining Attack Pattern Text
5 Attack Chains
6 Attack Pattern Hierarchies
7 Analytic Environment
8 Summary
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