1 сент. 2015 г. · I want to create an algorithm that performs a fuzzy search on a list of names of schools. This is what I have looked at so far.

16 мая 2019 г. · Levenshtein- and Damerau–Levenshtein distance are both good metrics for string similarity, but make sure that you use a fast implementation.

16 апр. 2015 г. · I need to find a set of substrings (each about 32 characters) in a very large string ( about 100k) as fast as possible. I need the search to be fuzzy.

14 авг. 2019 г. · When comparing Strings I usually use the Levenshtein-Distance. You can find an implementation of the algorithm here.

21 июн. 2016 г. · I'm trying to detect the names of cities in paragraph of text, in the order they occur. We have a list of ~1 million location names.

17 окт. 2020 г. · Fuzzy search works by using mathematical formulae that calculate the distance (or similarity between) two words. One such commonly used method is called the ...

29 мар. 2022 г. · Given a set array, create a function that receives one argument and returns a new array containing only the values that start with either:

13 февр. 2014 г. · I now tried do a fuzzy search on the name field with a Levenshtein distance of 5 as follows: curl -XGET "http://localhost:9200/_search " -d' { "query": { " ...

18 авг. 2016 г. · I need to automatically match product names (food). The problem is similar to Fuzzy matching of product names.

21 февр. 2019 г. · The straight forward approach is to iterate over all strings, calculate the distance for each and keep only the best N while you iterate.