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https://issues.apache.org/jira/browse/LUCENE-8633?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Alan Woodward resolved LUCENE-8633.
-----------------------------------
       Resolution: Fixed
    Fix Version/s: master (9.0)
                   8.0

> Remove term weighting from interval scoring
> -------------------------------------------
>
>                 Key: LUCENE-8633
>                 URL: https://issues.apache.org/jira/browse/LUCENE-8633
>             Project: Lucene - Core
>          Issue Type: Improvement
>            Reporter: Alan Woodward
>            Assignee: Alan Woodward
>            Priority: Major
>             Fix For: 8.0, master (9.0)
>
>         Attachments: LUCENE-8633.patch, LUCENE-8633.patch
>
>
> IntervalScorer currently uses the same scoring mechanism as SpanScorer, 
> summing the IDF of all possibly matching terms from its parent 
> IntervalsSource and using that in conjunction with a sloppy frequency to 
> produce a similarity-based score.  This doesn't really make sense, however, 
> as it means that terms that don't appear in a document can still contribute 
> to the score, and appears to make scores from interval queries comparable 
> with scores from term or phrase queries when they really aren't.
> I'd like to explore a different scoring mechanism for intervals, based purely 
> on sloppy frequency and ignoring term weighting.  This should make the scores 
> easier to reason about, as well as making them useful for things like 
> proximity boosting on boolean queries.



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