Tuning BM25

One of the nice features of BM25 is that, unlike TF/IDF, it has two parameters that allow it to be tuned:

k1

This parameter controls how quickly an increase in term frequency results in term-frequency saturation. The default value is 

1.2. Lower values result in quicker saturation, and higher values in slower saturation.

b

This parameter controls how much effect field-length normalization should have. A value of 

0.0disables normalization completely, and a value of 

1.0 normalizes fully. The default is 

0.75.

The practicalities of tuning BM25 are another matter. The default values for k1 and b should be suitable for most document collections, but the optimal values really depend on the collection. Finding good values for your collection is a matter of adjusting, checking, and adjusting again.

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"

},        "body": {          "type":       "string",          "similarity": "default"

}      }  }}

	The title field uses BM25 similarity.
	The body field uses the default similarity (see ).

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 BM25

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": {

"type": "BM25",        "b":    0

}    }  },  "mappings": {    "doc": {      "properties": {        "title": {          "type":       "string",          "similarity": "my_bm25"

},        "body": {          "type":       "string",          "similarity": "BM25"

}      }    }  }} 参考：https://www.elastic.co/guide/en/elasticsearch/guide/current/changing-similarities.html