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 TF/IDF, such as `BM25`.

Similarities are mostly useful for <<string,`string`>> fields, especially
`analyzed` string 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:

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

`BM25`::
        The Okapi BM25 algorithm.
        See {defguide}/pluggable-similarites.html[Plugggable Similarity Algorithms]
        for more information.


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

[source,js]
--------------------------------------------------
PUT my_index
{
  "mappings": {
    "my_type": {
      "properties": {
        "default_field": { <1>
          "type": "string"
        },
        "bm25_field": {
          "type": "string",
          "similarity": "BM25" <2>
        }
      }
    }
  }
}
--------------------------------------------------
// AUTOSENSE
<1> The `default_field` uses the `classic` similarity (ie TF/IDF).
<2> The `bm25_field` uses the `BM25` similarity.