TL;DR: Why score addition is recommended in examples when using these?
Doesn't that make the resulting score sensible to the number of boolean
clauses?
I've been reading about feature fields (in particular the "dynamic"
feature field you get with LongPoint.newDistanceFeatureQuery(), for
adding a "recency" factor), and I see the recommended usage is to *add*
that query to a boolean, like this: termquery1 should(featureQuery).
As BooleanQuery adds the score of the clauses in other queries the
infuence of the clauses will vary, e.g.: If the query is: termquery1
termquery2 should(featureQuery) .... then the score contribution of the
feature field will be more diluted and the recency will be less
relevant. That seems wrong. Wouldn't it be more appropriate to multiply
the entirety of the score by a "recency" factor (got from the "feature
field query")?
How this recency thing is normally implemented?
Thanks!
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