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The similarity algorithm can be set on a per-field basis. It’s just a matter of specifying the chosen algorithm in the field’s mapping:
PUT /my_index
{
"mappings": {
"doc": {
"properties": {
"title": {
"type": "string",
"similarity": "BM25" (1)
},
"body": {
"type": "string",
"similarity": "default" (2)
}
}
}
}
The title field uses BM25 similarity.
The body field uses the default similarity (see [practical-scoring-function]).
Currently, it is not possible to change the similarity mapping for an
existing field. You would need to reindex your data in order to do that.
Configuring a similarity is much like configuring an analyzer. Custom similarities can be specified when creating an index. For instance:
PUT /my_index
{
"settings": {
"similarity": {
"my_bm25": { (1)
"type": "BM25",
"b": 0 (2)
}
}
},
"mappings": {
"doc": {
"properties": {
"title": {
"type": "string",
"similarity": "my_bm25" (3)
},
"body": {
"type": "string",
"similarity": "BM25" (4)
}
}
}
}
}
Create a custom similarity called my_bm25, based on the built-in BM25 similarity.
Disable field-length normalization. See [bm25-tunability].
Field title uses the custom similarity my_bm25.
Field body uses the built-in similarity BM25.
|
Tip
|
A custom similarity can be updated by closing the index, updating the index settings, and reopening the index. This allows you to experiment with different configurations without having to reindex your documents. |
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