#!/usr/bin/env python print "Content-Type: text/html" print print """\

Hello World!

"""Using clustering techniques we divided words on the groups taking into account only their population distribution. As a distance between j-th and k-th words words we used Pearson’s distance:

pears_dist.png,
where the Pearson correlation coefficient between Bj and Bk populations:
ro.png.
The summation is over whole data pixel of given word map, σ i the standard deviation of B. The Pearson distance lies in [0, 2] range. Example of two words with small distance between them is [kl'osh] - vase for fruits and [rombambar] - rheum with D=0.08. They have very similar population distribution, see the maps below. Obviously their origin or coming to this area was happened on the same manner and epoch:
new_dialect253.pngnew_dialect137.png

Example of the pair of words with large distance near 2 is [trempel'] - сlothes hanger and [lekvar] - jam:
new_dialect595.png new_dialect514.png

On the base of information about Pearson distances between each words we clustered them and created following dendrogram:
Rplots.png