Per this post "theory behind relevance
scoring"
http://www.elastic.co/guide/en/elasticsearch/guide/current/scoring-theory.html
Elasticsearch calculate the field-length norm as follows:
norm(d) = 1 / √numTerms
But per my testing, seems the actual result value calculated does not meet
above formula.
Following is my index docs:
1.
{
"title" : "quick brown fox"
}
2.
{
"title" : "quick fox"
}
Then I query "fox" with following query:
POST /vsmtest/test/_search?explain
{
"query" : {
"match" : {"title":"fox"}
}
}
The result norm value are follows:
doc 1:
{
"value": 0.5,
"description": "fieldNorm(doc=0)"
}
doc 2:
{
"value": 0.625,
"description": "fieldNorm(doc=0)"
}
Can anyone help me understand how does 0.5 and 0.625 calculated per the
formula?
norm(d) = 1 / √numTerms
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