Elasticsearch mapping文档相似性算法

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).

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

巴特西

Elasticsearch mapping文档相似性算法

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