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Fuzzy search is an umbrella term for approximate matching in text retrieval. A common application is to compensate for typos in search phrases. In this Lunch Break, we take a look at different similarity measures and show how fuzzy search works in ArangoDB.

Watch this session to learn about:

  • (Damerau-)Levenshtein edit distance N-Grams and N-Gram Similarity
  • Fuzzy search with ArangoSearch using Views, Analyzers, and AQL functions.

Want to learn more about Fuzzy Search?
Check out interactive tutorial
View ArangoSearch documentation

Simran Spiller

About the Presenter:

Simran is a data modeling and migration enthusiast with a cultural sciences background. He is responsible for ArangoDB’s documentation, helps out with design questions, and supports the community, especially with AQL and JavaScript.