Elasticsearch allows you to configure a scoring algorithm or similarity per field. The similaritysetting provides a simple way of choosing a similarity algorithm other than the default TF/IDF, such as BM25.
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:
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BM25 - The Okapi BM25 algorithm. The algorithm used by default in Elasticsearch and Lucene. See Pluggable Similarity Algorithms for more information.
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classic - The TF/IDF algorithm which used to be the default in Elasticsearch and Lucene. See Lucene’s Practical Scoring Function for more information.
The similarity can be set on the field level when a field is first created, as follows:
PUT my_index
{
"mappings": { "my_type": { "properties": { "default_field": { 
"type": "text" }, "classic_field": { "type": "text", "similarity": "classic" } } } } }
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参考：https://www.elastic.co/guide/en/elasticsearch/reference/current/similarity.html
本文转自张昺华-sky博客园博客，原文链接：http://www.cnblogs.com/bonelee/p/6472719.html，如需转载请自行联系原作者
