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https://issues.apache.org/jira/browse/LUCENE-8563?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16687440#comment-16687440
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Michael Gibney commented on LUCENE-8563:
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[~jpountz], thanks for pointing out the work on BM25F. I'm interested to take a
closer look at that.
"Users could multiply their per-field boosts by (k1+1)?" ... thanks, yes! That
should work in a pinch, though I was so focused on the Similarity that I missed
the possibility of scaling it externally in this way.
Having k1's presence in the numerator be configurable (either as an extra
boolean parameter to the (modified) existing BM25Similarity, or something along
the lines of what [~softwaredoug] suggests) would make sense to me, regardless
of the benefits of the change (performance or otherwise).
> Remove k1+1 from the numerator of BM25Similarity
> -------------------------------------------------
>
> Key: LUCENE-8563
> URL: https://issues.apache.org/jira/browse/LUCENE-8563
> Project: Lucene - Core
> Issue Type: Improvement
> Reporter: Adrien Grand
> Priority: Minor
>
> Our current implementation of BM25 does
> {code:java}
> boost * IDF * (k1+1) * tf / (tf + norm)
> {code}
> As (k1+1) is a constant, it is the same for every term and doesn't modify
> ordering. It is often omitted and I found out that the "The Probabilistic
> Relevance Framework: BM25 and Beyond" paper by Robertson (BM25's author) and
> Zaragova even describes adding (k1+1) to the numerator as a variant whose
> benefit is to be more comparable with Robertson/Sparck-Jones weighting, which
> we don't care about.
> {quote}A common variant is to add a (k1 + 1) component to the
> numerator of the saturation function. This is the same for all
> terms, and therefore does not affect the ranking produced.
> The reason for including it was to make the final formula
> more compatible with the RSJ weight used on its own
> {quote}
> Should we remove it from BM25Similarity as well?
> A side-effect that I'm interested in is that integrating other score
> contributions (eg. via oal.document.FeatureField) would be a bit easier to
> reason about. For instance a weight of 3 in FeatureField#newSaturationQuery
> would have a similar impact as a term whose IDF is 3 (and thus docFreq ~= 5%)
> rather than a term whose IDF is 3/(k1 + 1).
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