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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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