Unverified50% confidenceFactExact time
Reciprocal 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).
1
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50%
Confidence
Long-term
Relevance
10/11/2026
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VerifiedThe 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.75% similarUnverifiedThe core formula of RRF is RRF_score(d) = Σ 1 / (k + rank_i(d)), where k is a smoothing constant commonly set to 60.66% similarUnverifiedThe first metric is Effective Rank, which measures in a continuous manner how many directions the Jacobian matrix truly acts upon.65% similarUnverifiedThe composite score of reports selected by the full composite objective rose to 0.4122.59% similarUnverifiedThe Top3 configuration achieved an accuracy of 97.148%, a weighted F1 of 97.055%, and an MCC of 0.9675, comprehensively outperforming the Full21 configuration using all 21 metrics (accuracy 95.999%, weighted F1 95.521%, MCC 0.9549).59% similar
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