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https://issues.apache.org/jira/browse/LUCENE-8343?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16505885#comment-16505885
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Alessandro Benedetti commented on LUCENE-8343:
----------------------------------------------

Hi Adrien,
I theoretically agree with you.
The reason I structured the patch this way is because what I noticed so far in 
my contributions is that a contribution is much more likely to be reviewed and 
accepted if it fixes a bug with the minimal impact as possible and involving 
less classes as possible.

The problem here is indeed related the data type of : 
- the suggestion score ( should be double)
- and weght ( should be Long as 0 must be considered different from null)

I would be more than happy to contribute that, but my feeling is that a patch 
that span over a lot of different classes and areas, would be ignored with the 
final result of the bug(s) to remain there.
Happy if you( the community in general) contradict me and I will proceed with 
the data types change approach :)

> BlendedInfixSuggester bad score calculus for certain suggestion weights
> -----------------------------------------------------------------------
>
>                 Key: LUCENE-8343
>                 URL: https://issues.apache.org/jira/browse/LUCENE-8343
>             Project: Lucene - Core
>          Issue Type: Bug
>          Components: core/search
>    Affects Versions: 7.3.1
>            Reporter: Alessandro Benedetti
>            Priority: Major
>         Attachments: LUCENE-8343.patch, LUCENE-8343.patch, LUCENE-8343.patch
>
>          Time Spent: 20m
>  Remaining Estimate: 0h
>
> Currently the BlendedInfixSuggester return a (long) score to rank the 
> suggestions.
> This score is calculated as a multiplication between :
> long *Weight* : the suggestion weight, coming from a document field, it can 
> be any long value ( including 1, 0,.. )
> double *Coefficient* : 0<=x<=1, calculated based on the position match, 
> earlier the better
> The resulting score is a long, which means that at the moment, any weight<10 
> can bring inconsistencies.
> *Edge cases* 
> Weight =1
> Score = 1( if we have a match at the beginning of the suggestion) or 0 ( for 
> any other match)
> Weight =0
> Score = 0 ( independently of the position match coefficient)



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