Okay - think I was a tad off base -
Here is the cosine def used:
cos(a) = V(q) dot V(d) / |V(q)||V(d)|
So the cosine is the query vector dot the document vector divided by the magnitude of the vectors. Classically, |V(q)||V(d)| is a normalization factor that takes the vectors to unit vectors (so you get the real cosine)
This is because the magnitude of a unit vector is 1 be definition.
But we don't care about absolute numbers, just relative numbers (as has been often pointed out) - so the IR guys already fudge this stuff.
While I thought that the queryNorm correlates to |V(q)||V(d)| before, I was off - its just |V(q)|. |V(d)| is replaced with the document length normalization, a much faster calculation with similar properties - a longer doc would have a larger magnitude most likely. edit not just similar properties - but many times better properties - the standard normalization would not factor in document length at all - it essentially removes it.
So one strategy is just to not normalize query - though the lit i see doing this is very inefficiently calculating the query norm in the inner loop - we are not doing that, and so its not much of an optimization for us.
cos(a) = V(q) dot V(d) / |V(d)| == cos(a) * |V(q)| = v(q) dot v(d)
And it does make queries more comparable (an odd goal I know, but for free?)
Sorry I was a little off earlier - just tried to learn all this myself - and linear alg was years ago - and open book tests lured my younger, more irresponsible self to not go to the classes ...
Anyhow, thats my current understanding - please point out if you know I have something wrong.