That is a nice summary.
A couple of thoughts to add for those who aren't information-retrieval
nerds (this helped solidify TF and IDF in my head >20 years ago):
* I like to think of TF (whatever it's formulation) as how *characteristic *a
term is for a document. "dog" occurs once, then this article isn't really
* Similarly, IDF is how *distinctive* a term is for a document. "the" shows
up a lot in English text—so it is characteristic—but it shows up in every
text, so it isn't distinctive.
So, in a corpus of English documents, "the" is characteristic (high TF) but
not distinctive (low IDF) for any given document. OTOH, in a corpus that's
99% Swahili documents, and a small handful of English documents, "the" is
both characteristic (because the docs are in English) and distinctive
(because most other docs are not).
Thus, TF is about a given document, and IDF is about the corpus it is part
* Those cool graphs in that blog post? Those were obviously done with
Desmos ( https://www.desmos.com
) a powerful free HTML5 graphing
calculator. We use it to look at scoring components to understand how
different formulas behave, and how modifying various parameters affects
them. I use it so much, I just wanted to share it.
Software Engineer, Discovery
On Fri, Mar 18, 2016 at 7:36 AM, Guillaume Lederrey <glederrey(a)wikimedia.org
> Yep, nice reading!
> On Fri, Mar 18, 2016 at 12:28 AM, Dan Garry <dgarry(a)wikimedia.org
> > This was a really helpful read
for me! Thanks for sending. :-)
> > Dan
> > On 14 March 2016 at 16:21, Tomasz Finc <tfinc(a)wikimedia.org
> >> Here is a good write up that breaks it down
> >> Given the recent threads about exploring BM25, i thought this was a
> >> good introduction to the difference between the two.
> >> Cheers.
> >> --tomasz