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 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 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 Pluggable Similarity Algorithms for more information.
-
classic - The TF/IDF algorithm which used to be the default in Elasticsearch and Lucene. See 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:
PUT my_index
{
"mappings": {
"properties": {
"default_field": { 
"type": "text"
},
"boolean_sim_field": {
"type": "text",
"similarity": "boolean" 
}
}
}
}
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