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https://issues.apache.org/jira/browse/SOLR-14560?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17133592#comment-17133592
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Alessandro Benedetti commented on SOLR-14560:
---------------------------------------------
The draft is attached :
[https://github.com/apache/lucene-solr/pull/1571|https://github.com/apache/lucene-solr/pull/1571]
Any comments on the architectural changes and the places I touched so far are
more than welcome.
Bear in mind the task is still work in progress and changes/tests will happen,
so in case you are curious and willing to leave a comment, take this into
account.
Once ready for code review I will add a comment here a finalise the Pull
Request from draft.
I will proceed to the merge with at least another committer approval.
I tag all the people that worked on Learning To Rank, in no particular order:
[~cpoerschke] [~diegoceccarelli] [~mnilsson]
[~jpantony][~jdorando][~nsanthapuri] [~dave1g]
> Learning To Rank Interleaving
> -----------------------------
>
> Key: SOLR-14560
> URL: https://issues.apache.org/jira/browse/SOLR-14560
> Project: Solr
> Issue Type: New Feature
> Security Level: Public(Default Security Level. Issues are Public)
> Components: contrib - LTR
> Affects Versions: 8.5.2
> Reporter: Alessandro Benedetti
> Priority: Minor
> Time Spent: 10m
> Remaining Estimate: 0h
>
> Interleaving is an approach to Online Search Quality evaluation that can be
> very useful for Learning To Rank models:
> [https://sease.io/2020/05/online-testing-for-learning-to-rank-interleaving.html|https://sease.io/2020/05/online-testing-for-learning-to-rank-interleaving.html]
> Scope of this issue is to introduce the ability to the LTR query parser of
> accepting multiple models (2 to start with).
> If one model is passed, normal reranking happens.
> If two models are passed, reranking happens for both models and the final
> reranked list is the interleaved sequence of results coming from the two
> models lists.
> As a first step it is going to be implemented through:
> TeamDraft Interleaving with two models in input.
> In the future, we can expand the functionality adding the interleaving
> algorithm as a parameter.
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