The weights you express could flag a probabilistic view or your final score.
The model you quoted will calculate the final score as :
0.9*scorePersonalId +0.1* originalScore
The final score will NOT necessarily be 0https://lucene.apache.org/solr/guide/6_6/the-dismax-query-parser.html#the-dismax-q
you to reassign a
> > new score to the top N documents returned by your query and then reorder
> them based on that (ignoring the original score, if you want).
> >
> > Cheers,
> > Diego
> >
> > [1] https://cwiki.apache.org/confluence/display/solr/Learning+To+Ra
+To+Rank
>
> From: solr-user@lucene.apache.org At: 09/21/17 08:49:13
> To: solr-user@lucene.apache.org
> Subject: Re: Rescoring from 0 - full
>
> Hi Dariusz,
> You could use fq for filtering (can disable caching to avoid polluting filter
> cache) and q=*:*. That way you’ll g
e.org
Subject: Re: Rescoring from 0 - full
Hi Dariusz,
You could use fq for filtering (can disable caching to avoid polluting filter
cache) and q=*:*. That way you’ll get score=1 for all doc and can rerank. The
issue with this approach is that you rerank top N and without score they
wouldn’t be order
Hi Dariusz,
You could use fq for filtering (can disable caching to avoid polluting filter
cache) and q=*:*. That way you’ll get score=1 for all doc and can rerank. The
issue with this approach is that you rerank top N and without score they
wouldn’t be ordered so it is no-go.
What you could do (
Hi,
When I use boosting fuctionality, it is always about adding or
multiplicating the score calculated in the 'q' param.
I mau use function queries inside 'q', but this may hit performance on
calling multiple nested functions.
I thaught that 'rerank' could help, but it is still about changing the
o
