Language Intelligence

Akshi Kumar is a Senior Lecturer and Director for Post-Graduate Research with the Department of Computing at Goldsmiths, University of London, UK. Dr. Kumar earned her PhD in Computer Science & Engineering from the University of Delhi, India, in 2011, and her research interests include sentiment analysis, affective computing, cyber-informatics, psychometric NLP, and more. She has been ranked #8 globally for Sentiment Analysis over the past 5 years by ScholarGPS. Her name has been included in the “Top 2% scientist of the world” list by Stanford University, USA in 2023, 2022 and 2021.

• List of Figures xiiiList of Tables xvAbout the Author xviiPreface xixAcknowledgements xxi1 Foundations of Natural Language Processing 11.1 History of NLP 31.2 Approaches to NLP 51.3 Understanding NLP through NLU and NLG: Examples and Case Studies 91.3.1 Practical Case Studies 91.4 NLP Pipeline 101.5 NLP’s Transformative Impact on Business and Society 122 Navigating the Data Landscape for NLP 152.1 Types of Data in NLP 162.2 Data Acquisition 172.3 Challenges in NLP Data Acquisition and Management 212.4 Data Quality Check in NLP 222.5 Ethical Considerations in NLP Data Management 253 Fundamental Text Processing 313.1 Text Cleaning 323.2 Sentence Splitting 343.3 Tokenization 363.4 Lemmatization and Stemming 443.5 StopWord Removal 483.6 Part-of-Speech Tagging 493.7 Parsing and Syntactic Analysis 503.8 Tools and Libraries for Text Processing 564 Linguistic Features in NLP 634.1 Levels of Linguistic Analysis 644.2 Features in NLP 734.3 Vector Space Representation in NLP 754.4 Semantic Features in NLP 814.5 Feature Generation in NLP: Manual versus Automatic Approaches 895 Computational and Cognitive Approaches in Natural Language Processing 955.1 Machine Learning for NLP 975.2 Memory and Recall Models 1005.3 Attention Mechanisms 1055.4 Human-Like Reasoning 1125.5 Transfer Learning in NLP 1145.6 Learning with Minimal Examples 1225.7 Neuro-Symbolic Approaches 1236 Fundamental Language Processing Techniques 1296.1 Topic Modelling and Subject Identification 1296.2 Named Entity Recognition 1366.3 Text Coherence and Cohesion 1446.4 Stylistic Analysis 1516.5 Semantic Role Labelling 1547 Natural Language Processing for Affective, Psychological, and Content Analysis 1597.1 Sentiment Analysis: Dissecting Text for Opinion Mining 1597.2 Emotion Recognition: Beyond Polarity 1687.3 Irony and Sarcasm Detection: Between the Lines 1757.4 Humor Identification in Text: Tapping into Textual Tickle 1807.5 Psychometric NLP 1847.6 Learning Disabilities Detection 1907.7 Textual Indicators of Distress: Addressing Depression, Anxiety, and Beyond 1947.8 Digital Content Moderation using NLP 1988 Multilingual Natural Language Processing 2238.1 Translation and Transliteration 2238.2 Cross-Lingual Models and Embeddings 2288.3 Low-Resource Language Processing 2358.4 Cultural Nuance and Idiom Recognition in Natural Language Processing 2409 Domain-Specific Natural Language Processing 2439.1 Healthcare Natural Language Processing 2439.2 Legal Natural Language Processing 2509.3 Finance Natural Language Processing 2559.4 NLP in Education 26210 Measuring Success in Natural Language Processing Evaluation and Metrics 26910.1 Intrinsic versus Extrinsic Evaluation Techniques 26910.2 Extrinsic Evaluation Techniques 27010.3 Metrics for Text Classification 27210.4 Evaluating Machine Translation and Text Summarization 27610.5 Metrics for Question-Answering and Conversational AI 27810.5.1 Evaluation in Ranking and Information Retrieval 27910.6 Metrics for Text-Based Forecasting and Prediction 280Knowledge Checkpoint Answers 285A Text Representation Techniques: A Unified Overview 305B Step-by-Step Guide to NLP Processing on E-Commerce Customer Feedback 307C Harnessing Python Libraries for NLP 311Further Reading 313Index 315