Elasticsearch mapping文檔相似性算法

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:

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.

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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	The default_field uses the BM25 similarity.
	The classic_field uses the classic similarity (ie TF/IDF).

 

參考：https://www.elastic.co/guide/en/elasticsearch/reference/current/similarity.html