Rank features field typeedit
A rank_features field can index numeric feature vectors, so that they can
later be used to boost documents in queries with a
rank_feature query.
It is analogous to the rank_feature data type but is better suited
when the list of features is sparse so that it wouldn’t be reasonable to add
one field to the mappings for each of them.
PUT my-index-000001
{
"mappings": {
"properties": {
"topics": {
"type": "rank_features"
},
"negative_reviews" : {
"type": "rank_features",
"positive_score_impact": false
}
}
}
}
PUT my-index-000001/_doc/1
{
"topics": {
"politics": 20,
"economics": 50.8
},
"negative_reviews": {
"1star": 10,
"2star": 100
}
}
PUT my-index-000001/_doc/2
{
"topics": {
"politics": 5.2,
"sports": 80.1
},
"negative_reviews": {
"1star": 1,
"2star": 10
}
}
GET my-index-000001/_search
{
"query": {
"rank_feature": {
"field": "topics.politics"
}
}
}
GET my-index-000001/_search
{
"query": {
"rank_feature": {
"field": "negative_reviews.1star"
}
}
}
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Rank features fields must use the |
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Rank features that correlate negatively with the score need to declare it |
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Rank features fields must be a hash with string keys and strictly positive numeric values |
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This query ranks documents by how much they are about the "politics" topic. |
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This query ranks documents inversely to the number of "1star" reviews they received. |
rank_features fields only support single-valued features and strictly
positive values. Multi-valued fields and zero or negative values will be rejected.
rank_features fields do not support sorting or aggregating and may
only be queried using rank_feature queries.
rank_features fields only preserve 9 significant bits for the
precision, which translates to a relative error of about 0.4%.
Rank features that correlate negatively with the score should set
positive_score_impact to false (defaults to true). This will be used by
the rank_feature query to modify the scoring formula
in such a way that the score decreases with the value of the feature instead of
increasing.