Jan Urbański <wulczer@wulczer.org> writes:
> On 29/05/10 17:09, Tom Lane wrote:
>> There is definitely something wrong with your math there. It's not
>> possible for the 100'th most common word to have a frequency as high
>> as 0.06 --- the ones above it presumably have larger frequencies,
>> which makes the total quite a lot more than 1.0.
> Upf... hahaha, I computed this as 1/(st + 10)*H(W), where it should be
> 1/((st + 10)*H(W))... So s would be 1/(110*6.5) = 0.0014
Um, apparently I can't do simple arithmetic first thing in the morning
either, cause I got my number wrong too ;-)
After a bit more research: if you use the basic form of Zipf's law
with a 1/k distribution, the first frequency has to be about 0.07
to make the total come out to 1.0 for a reasonable number of words.
So we could use s = 0.07 / K when we wanted a final list of K words.
Some people (including the LC paper) prefer a higher exponent, ie
1/k^S with S around 1.25. That makes the F1 value around 0.22 which
seems awfully high for the type of data we're working with, so I think
the 1/k rule is probably what we want here.
regards, tom lane
