Fuzzy string matching using Levenshtein algorithm in Elasticsearch

Question

I have just started exploring Elasticsearch. I created a document as follows:

curl -XPUT "http://localhost:9200/cities/city/1" -d'
{
    "name": "Saint Louis"

}'

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": {
       "fuzzy": {
           "name" : {
               "value" : "St. Louis",
               "fuzziness" : 5
           }

       }
    }
}'

But its not returning any match. I expect the Saint Louis record to be returned. How can i fix my query ?

Thanks.

Akshay · Accepted Answer · 2014-02-13 09:59:56Z

3

The problem with your query is that only a maximum edit distance of 2 is allowed.

In the case above what you probably want to do is have a synonym for St. to Saint, and that would match for you. Of course, this would depend on your data as St could also be "street".

If you want to just test the fuzzy searching, you could try this example

curl -XGET "http://localhost:9200/_search " -d'
{
    "query": {
       "fuzzy": {
           "name" : {
               "value" : "Louiee",
               "fuzziness" : 2
           }

       }
    }
}

edited Feb 13, 2014 at 9:59

answered Feb 13, 2014 at 9:53

Akshay

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3 Comments

Tzvi Gregory Kaidanov Over a year ago

I have a query with should with function_score with fuzziness 0.75 with multi_match with cross_field My query is a term without one last character - for instance "NAM" instead of "NAME" By fuzziness rules it must be returned to me , but I don't get results. What would you suggest on this matter? Is there a way around without NGRAM ?

Akshay Over a year ago

Gregory, it would probably be best to post that as a new question, along with details of your mapping and query.

Giriraj Sharma Over a year ago

@Gregory fuzziness is not supported for cross_field type multi_match queries.

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