Alessandro Benedetti created SOLR-17319:
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Summary: Introduce support for Reciprocal Rank Fusion (combining
queries)
Key: SOLR-17319
URL: https://issues.apache.org/jira/browse/SOLR-17319
Project: Solr
Issue Type: New Feature
Security Level: Public (Default Security Level. Issues are Public)
Components: query
Affects Versions: 9.6.1
Reporter: Alessandro Benedetti
Reciprocal Rank Fusion (RRF) is an algorithm that takes in input multiple
ranked lists to produce a unified result set.
Examples of use cases where RRF can be used include hybrid search and multiple
Knn vector queries executed concurrently.
RRF is based on the concept of reciprocal rank, which is the inverse of the
rank of a document in a ranked list of search results.
The combination of search results happens taking into account the position of
the items in the original rankings, and giving higher score to items that are
ranked higher in multiple lists. RRF was introduced the first time by Cormack
et al. in [1].
[1] Cormack, Gordon V. et al. “Reciprocal rank fusion outperforms condorcet and
individual rank learning methods.” Proceedings of the 32nd international ACM
SIGIR conference on Research and development in information retrieval (2009)
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