Robert Muir commented on LUCENE-8197:

FWIW: the computePivotFeatureValue helper makes perfect sense to me. Its just 
computeSensibleWeight that has me really confused.

> Make top-k queries fast when static scoring signals are incorporated into the 
> score
> -----------------------------------------------------------------------------------
>                 Key: LUCENE-8197
>                 URL: https://issues.apache.org/jira/browse/LUCENE-8197
>             Project: Lucene - Core
>          Issue Type: Improvement
>            Reporter: Adrien Grand
>            Priority: Minor
>             Fix For: master (8.0)
>         Attachments: LUCENE-8197.patch, LUCENE-8197.patch, LUCENE-8197.patch
> Block-max WAND (LUCENE-8135) and some earlier issues made Lucene faster at 
> computing the top-k matches of boolean queries.
> It is quite frequent that users want to improve ranking and end up scoring 
> with a formula that could look like {{bm25_score + w * log(alpha + 
> pagerank)}} (w and alpha being constants, and pagerank being a per-document 
> field value). You could do this with doc values and {{FunctionScoreQuery}} 
> but unfortunately this will remove the ability to optimize top-k queries 
> since the scoring formula becomes opaque to Lucene.
> I'd like to add a new field that allows to store such scoring signals as term 
> frequencies, and new queries that could produce {{log(alpha + pagerank)}} as 
> a score. Then implementing the above formula can be done by boosting this 
> query with a boost equal to {{w}} and adding this boosted query as a SHOULD 
> clause of a {{BooleanQuery}}. This would give Lucene the ability to compute 
> top-k hits faster, especially but not only if the index is sorted by 
> decreasing pagerank.

This message was sent by Atlassian JIRA

To unsubscribe, e-mail: dev-unsubscr...@lucene.apache.org
For additional commands, e-mail: dev-h...@lucene.apache.org

Reply via email to