Alessandro Benedetti created SOLR-14560:
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Summary: 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
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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