OpenSearch/docs/reference/mapping/params/similarity.asciidoc

[[similarity]]
=== `similarity`

Elasticsearch allows you to configure a scoring algorithm or _similarity_ per
field. The `similarity` setting provides a simple way of choosing a similarity
algorithm other than the default `BM25`, such as `TF/IDF`.

Similarities are mostly useful for <<text,`text`>> fields, but can also apply
to other field types.

Custom similarities can be configured by tuning the parameters of the built-in
similarities. For more details about this expert options, see the
<<index-modules-similarity,similarity module>>.

The only similarities which can be used out of the box, without any further
configuration are:

`BM25`::
        The Okapi BM25 algorithm. The algorithm used by default in Elasticsearch and Lucene.
        See {defguide}/pluggable-similarites.html[Pluggable Similarity Algorithms]
        for more information.

`classic`::
        The TF/IDF algorithm which used to be the default in Elasticsearch and
        Lucene. See {defguide}/practical-scoring-function.html[Lucene’s Practical Scoring Function]
        for more information.

`boolean`::
        A simple boolean similarity, which is used when full-text ranking is not needed
        and the score should only be based on whether the query terms match or not.
        Boolean similarity gives terms a score equal to their query boost.


The `similarity` can be set on the field level when a field is first created,
as follows:

[source,js]
--------------------------------------------------
PUT my_index?include_type_name=true
{
  "mappings": {
    "_doc": {
      "properties": {
        "default_field": { <1>
          "type": "text"
        },
        "boolean_sim_field": {
          "type": "text",
          "similarity": "boolean" <2>
        }
      }
    }
  }
}
--------------------------------------------------
// CONSOLE
<1> The `default_field` uses the `BM25` similarity.
<2> The `boolean_sim_field` uses the `boolean` similarity.