Verified65% confidenceFactTime unknown
The Reciprocal Rank Fusion (RRF) algorithm was proposed by Cormack et al. in 2009, with a core formula of Score = Σ 1/(k + rank_i), where k typically takes the value 60 as a smoothing constant.
3
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65%
Confidence
Long-term
Relevance
5/31/2026
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Related Claims
UnverifiedThe core formula of RRF is RRF_score(d) = Σ 1 / (k + rank_i(d)), where k is a smoothing constant commonly set to 60.77% similarUnverifiedReciprocal Rank Fusion (RRF) computes the final score for each document by summing the reciprocal of its rank in each ranked list plus a smoothing constant k (typically set to 60).75% similarUnverifiedThe RRF fusion formula is score += weight / (k + rank + 1), with k_constant set to 60, dense weight 0.7, and sparse weight 0.3.69% similarUnverifiedThe first metric is Effective Rank, which measures in a continuous manner how many directions the Jacobian matrix truly acts upon.69% similarUnverifiedReciprocal Rank@k is defined as the reciprocal of the rank of the first relevant result: ranking first gives 1 point, ranking third gives 1/3 point, and having none at all gives 0 points.63% similar
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