Hi,
Your answers have helped me a lot.
I've managed to use the LTRQParserPlugin and it does what I need. Full
control over scoring with it's re-ranking functionality.
I define my custom features and may pass custom params to them using the
"efi.*" syntax.
Is there something similar to define weights in the model that uses these
features?
Can I have single model, byt pass feature weights in each request?
How do I pass my custom weights with each request in the example below?
{
"store" : "myFeaturesStore",
"name" : "myModel",
"class" : "org.apache.solr.ltr.model.LinearModel",
"features" : [
{ "name" : "scorePersonalId" },
{ "name" : "originalScore" }
],
"params" : {
"weights" : {
"scorePersonalId" : 0.9,
"originalScore" : 0.1
}
}
}
I am using SOLR 6.6, soon switching to 7.0
Best regards,
Dariusz Wojtas
On Thu, Sep 21, 2017 at 5:18 PM, Erick Erickson <erickerick...@gmail.com>
wrote:
> Sure, you can take full control of the scoring, just write a custom
> similarity.
>
> What's not at all clear is why you want to. RerankQParserPlugin will
> re-rank the to N documents by pushing them through a different query,
> can you make that work?
>
> Best,
> Erick
>
>
>
> On Thu, Sep 21, 2017 at 4:20 AM, Diego Ceccarelli (BLOOMBERG/ LONDON)
> <dceccarel...@bloomberg.net> wrote:
> > Hi Dariusz,
> > If you use *:* you'll rerank only the top N random documents, as Emir
> said, that will not produce interesting results probably.
> > If you want to replace the original score, you can take a look at the
> learning to rank module [1], that would allow 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+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 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 (did not try) in rescoring divide by score (not sure
> if can access calculated but could calculate) to eliminate score.
> >
> > HTH,
> > Emir
> >
> >> On 20 Sep 2017, at 21:38, Dariusz Wojtas <dwoj...@gmail.com> wrote:
> >>
> >> 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
> >> original score, not full calculation.
> >>
> >> How can take full control on score in rerank? Is it possible?
> >>
> >> Best regards,
> >> Dariusz Wojtas
> >
> >
>
