Reputation: 4178
Right now my search gives me unwanted results when I search, say for "egg". I get following:
_score: 2.7645843
_source:
django_id: "18003"
text: "Bagels, egg"
content_auto: "Bagels, egg"
django_ct: "web.fooddes"
allergies: []
outdated: false
id: "web.fooddes.18003"
_explanation:
value: 2.7645843
description: "weight(_all:egg in 516) [PerFieldSimilarity], result of:"
details:
- value: 2.7645843
description: "fieldWeight in 516, product of:"
details:
- value: 1.4142135
description: "tf(freq=2.0), with freq of:"
details:
- value: 2.0
description: "termFreq=2.0"
- value: 5.21295
description: "idf(docFreq=26, maxDocs=1824)"
- value: 0.375
description: "fieldNorm(doc=516)"
as the first result.
And only as fifth or even further the wanted one:
_score: 2.380459
_source:
django_id: "01124"
text: "Egg, white, raw, fresh"
content_auto: "Egg, white, raw, fresh"
django_ct: "web.fooddes"
allergies: []
outdated: false
id: "web.fooddes.01124"
_explanation:
value: 2.3804593
description: "weight(_all:egg in 1489) [PerFieldSimilarity], result of:"
details:
- value: 2.3804593
description: "score(doc=1489,freq=2.0), product of:"
details:
- value: 0.99999994
description: "queryWeight, product of:"
details:
- value: 5.386365
description: "idf(docFreq=22, maxDocs=1848)"
- value: 0.18565395
description: "queryNorm"
- value: 2.3804595
description: "fieldWeight in 1489, product of:"
details:
- value: 1.4142135
description: "tf(freq=2.0), with freq of:"
details:
- value: 2.0
description: "termFreq=2.0"
- value: 5.386365
description: "idf(docFreq=22, maxDocs=1848)"
- value: 0.3125
description: "fieldNorm(doc=1489)"
That is because the first result has less words in it and consequently the result has higher score, because "egg" is more relevant in this case.
However, I want the first word encountered in the result to be the most important. So if I search for word "egg", it should first and foremost show those results that start with this word. Any ideas how to implement this?
Upvotes: 3
Views: 1057
Reputation: 4178
Figured it out thanks to people at https://discuss.elastic.co.
"query": {
"bool": {
"must": { "match": { "_all": request_text }},
"should":
{
"span_first" : {
"match" : {
"span_term" : { "_all" : request_text }
},
"end" : 1
}
}
}
}
Upvotes: 3