As the title states, what exactly in Elasticsearch's fuzzy-query is related to fuzzy logic?
For example, given a string, a fuzzy query with fuzziness of 2 will return all indexed strings that have a Levenshtein distance of 2. How does the system decide what answers to return if there are multiple matches?
Is there a fuzzy system behind it? one that has triangular functions (for instance) and can be expressed in something like this:
1| A B | /\ /\ A = fuzzy set 1 | / \/ \ B = fuzzy set 2 | / /\ \ 0|/ / \ \ ------------ a b c d
I would like a more theoretical answer that tackles what exactly in fuzzy queries is so fuzzy?