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Tuning BM25
One of the nice features of BM25 is that, unlike TF/IDF, it has two parameters that allow it to be tuned:
- 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. - This parameter controls how much effect field-length normalization should have. A value of
0.0disables normalization completely, and a value of1.0normalizes fully. The default is0.75.
k1 b 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" 
} } }}
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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
本文转自张昺华-sky博客园博客，原文链接：http://www.cnblogs.com/bonelee/p/6472828.html，如需转载请自行联系原作者