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Equation 8 · Part 4 · From BM25 to Agentic Retrieval: A History of Retrieval-Augmented Generation

Symbol f

score(D,Q)=∑qi∈QIDF(qi)⋅f(qi,D)⋅(k1+1)f(qi,D)+k1⋅(1−b+b⋅∣D∣avgdl),\mathrm{score}(D, Q) = \sum_{q_i \in Q} \mathrm{IDF}(q_i) \cdot \frac{f(q_i, D) \cdot (k_1 + 1)}{f(q_i, D) + k_1 \cdot \left(1 - b + b \cdot \dfrac{|D|}{\mathrm{avgdl}}\right)},
ff

What this part means

the frequency of query term qiq_i in D , |D| is the document’s length, avgdl\mathrm{avgdl} is the average document length in the collection, and k1k_1.

Its job in the formula

f is one of the signed contributions combined to compute the quantity on the left.

Where the article explains it

where f(qiq_i, D) is the frequency of query term qiq_i in D , |D| is the document’s length, avgdl\mathrm{avgdl} is the average document length in the collection, and k1k_1 and b are tuned constants controlling term-frequency saturation and length normalization respectively.

The passage around this formula

…field came to call BM25 — “Best Match 25,” after its position in a numbered sequence of variants the group had tried. Written in its now-standard form, a document D scores against a query Q as score(D,Q)=∑qi∈QIDF(qi)⋅f(qi,D)⋅(k1+1)f(qi,D)+k1⋅(1−b+b⋅∣D∣avgdl)\mathrm{score}(D, Q) = \sum_{q_i \in Q} \mathrm{IDF}(q_i) \cdot \frac{f(q_i, D) \cdot (k_1 + 1)}{f(q_i, D) + k_1 \cdot \left(1 - b + b \cdot \dfrac{|D|}{\mathrm{avgdl}}\right)}. where f(qiq_i, D) is the frequency of query term qiq_i in D , |D| is the document’s length, avgdl\mathrm{avgdl} is the average document length in the collection, and k1k_1 and b are tuned constants controlling term-frequency saturation and length normalization respectively. The saturation term is the substantive…

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Learn the underlying idea

A function assigns an output to each allowed input. The expression f(x) means “apply f to x”.

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Sources cited in the surrounding passage

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