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I have often come across this weighting scheme for tf-idf (term frequency - inverse document frequency) in text mining. I am wondering where it came from (for citations). I've searched very rigorously, but can't seem to find anything. Specifically, this is the weighting scheme:

$$ {\rm tfidf}(t,d,D)=(1+\log({f_{t,d})})\cdot \log\!\bigg(1+\frac{N}{n_t}\bigg) \\ N=|D| $$

where $t$ is the query term, $d$ is the document, $D$ is set of documents, $n_t$ is the document frequency of $t$, $f_{t,d}$ is how many times $t$ appears in $d$

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    $\begingroup$ Please describe what all the notation in the equation means. $\endgroup$ – Greenparker May 15 '16 at 0:01
  • $\begingroup$ What's your question? Is it just a reference request? $\endgroup$ – Sycorax May 15 '16 at 19:40
  • $\begingroup$ @C11H17N2O2SNa Yes. Where did this come from? $\endgroup$ – aces May 15 '16 at 20:05
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I was also looking for a reference to justify my use of sublinear tf. I couldn't find where it originated from, but if you just need a reference you can use An introduction to information retrieval, 2009, C.D. Manning et al. Section 6.4 is on variant tf-idf functions that includes sublinear tf scaling.

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