I try to use ngram based solution as "shotgun approach" to get results
which are not covered by more precise analyzers.
Article describing this approach is for example here
Match query, it is working as expected including parameter
minimum_should_match (this parameter is very important to be able to
exclude matches of only one ngram from queried word).
1. Below is explanation of match query searching word "first" without
filtered(Text:fir Text:irs Text:rst)->cache(_type:item)
and with "minimum_should_match": "80%"
filtered((Text:fir Text:irs Text:rst)~2)->cache(_type:item)
- But if I try to use the same with match_phrase query and phrase "first
second" I'll get the same result with or without minimum_should_match
filtered(Text:"(fir irs rst) (sec eco con ond)")->cache(_type:item)
I 'am expecting (for minimum_should_match) something like
filtered(Text:"(fir irs rst)~2 (sec eco con ond)~3")->cache(_type:item)
In attached file, there is complete Marvel Sense code with example
Does anybody know if it is a bug or if it known limitation of used
Or maybe there is another way how to achieve better phrase query results in
combination with ngram analyzer.
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