Multi Match Query With Cut_off Not Scoring High Frequency Terms

Elastic Stack Elasticsearch
1

Hi,

My mapping looks like the following:

"mapping_cluster" : {
"mappings" : {
"articles" : {
"properties" : {
"alexaRank" : {
"type" : "long"
},
"content" : {
"type" : "string"
},
"description" : {
"type" : "string"
},
"imageURL" : {
"type" : "string"
},
"pubDate" : {
"type" : "date",
"format" : "strict_date_optional_time||epoch_millis"
},
"sourceName" : {
"type" : "string"
},
"title" : {
"type" : "string"
},
"url" : {
"type" : "string"
}
}
}
}
}

Using ES 2.3.4.

Now on using the following query:

Note: Although none of the terms are common terms, but for testing purposes i am working with such a low cut_off frequency.

Question 1:
I get back documents containing wiseman as expected, but the scoring only includes score for pubDate field and the term "wiseman" and not any of the other matching terms.
As i had understood, the cut-off frequency causes the match query to become a bool query , with must clauses(containing low freq. terms) & should clauses(containing high freq. terms).
In this case, thus, since some of the documents matching wiseman, also include the other terms, shouldn't there scores be added to the final score as well?

Question 2:
The cut_off frequency will compare to relative doc_frequencies (since it lies between 0 and 1)
The relative doc_frequencies will be (doc_freq)/(total num. docs) and not maxDocs. Is this correct?

2

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