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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.
- Cover1
- Copyright2
- How to read this book3
- Introduction4
- Chapter 1: The Name Matching Problem5
- Chapter 2: How Names Vary in the Real World6
- Chapter 3: Foundations of Fuzzy Logic7
- Chapter 4: From Fuzzy Logic to Fuzzy Matching8
- Chapter 5: Text Normalization for Names9
- Chapter 6: Character-Based Similarity10
- Chapter 7: Token-Based Similarity11
- Chapter 8: Phonetic Matching12
- Chapter 9: Nicknames, Aliases, and Name Dictionaries13
- Chapter 10: Designing Fuzzy Membership Functions14
- Chapter 11: Building Fuzzy Rule Systems for Name Matching15
- Chapter 12: Composite Scoring and Weighted Matching16
- Chapter 13: Thresholds, Gray Zones, and Human Review17
- Chapter 14: Evaluation Metrics and Test Sets18
- Chapter 15: Blocking, Indexing, and Scalability19
- Chapter 16: Machine Learning for Name Matching20
- Chapter 17: Embeddings and Neural Similarity21
- Chapter 18: Multilingual and Cross-Script Name Matching22
- Chapter 19: Error Analysis and System Improvement23
- Chapter 20: Practical Implementation in Python24
- Chapter 21: Production Deployment and Monitoring25
- Chapter 22: Privacy, Fairness, and Responsible Use26
- Chapter 23: End-to-End Case Studies27
- Conclusion28