What is Fuzzy Matching?

Fuzzy matching (FM), also known as fuzzy logic or approximate string matching, is an AI and machine learning technology that identifies similar but not identical elements in data table sets. It uses algorithms to navigate between absolute rules to find duplicate strings, words/entries, that do not immediately share the same characteristics. This technique assists in finding approximate matches even when certain words are misspelled, abbreviated, or omitted. There are various fuzzy name matching algorithms such as Levenshtein Distance (LD), Hamming distance (HD), and Damerau-Levenshtein distance to help bridge those gaps. FM has numerous real-world applications including deduplication, auto-suggest engines in search engines, and improving data management systems by reducing human error. However, it's important to choose the right algorithm and programming language for each use case to prevent errors when applying fuzzy logic to data matching.

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