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.