Table of contents

Fuzzy Name Matching

From string similarity and fuzzy logic to reliable real-world name matching systems

Read each section in order. Every title can be opened as a TheoryTrace document.

• Cover
• Copyright
• How to read this book
• Introduction
• Chapter 1: The Name Matching Problem
• Chapter 2: How Names Vary in the Real World
• Chapter 3: Foundations of Fuzzy Logic
• Chapter 4: From Fuzzy Logic to Fuzzy Matching
• Chapter 5: Text Normalization for Names
• Chapter 6: Character-Based Similarity
• Chapter 7: Token-Based Similarity
• Chapter 8: Phonetic Matching
• Chapter 9: Nicknames, Aliases, and Name Dictionaries
• Chapter 10: Designing Fuzzy Membership Functions
• Chapter 11: Building Fuzzy Rule Systems for Name Matching
• Chapter 12: Composite Scoring and Weighted Matching
• Chapter 13: Thresholds, Gray Zones, and Human Review
• Chapter 14: Evaluation Metrics and Test Sets
• Chapter 15: Blocking, Indexing, and Scalability
• Chapter 16: Machine Learning for Name Matching
• Chapter 17: Embeddings and Neural Similarity
• Chapter 18: Multilingual and Cross-Script Name Matching
• Chapter 19: Error Analysis and System Improvement
• Chapter 20: Practical Implementation in Python
• Chapter 21: Production Deployment and Monitoring
• Chapter 22: Privacy, Fairness, and Responsible Use
• Chapter 23: End-to-End Case Studies
• Conclusion