Left Nb. | Right Nb. | Frequency |
---|---|---|
to | a | 4416 |
to | the | 14516 |
of | a | 5789 |
of | the | 32200 |
and | a | 3196 |
and | the | 8020 |
in | a | 8473 |
in | the | 30792 |
that | is | 1273 |
that | the | 5652 |
for | a | 4801 |
for | the | 11460 |
is | the | 3239 |
is | that | 1223 |
is | a | 4919 |
on | a | 3272 |
on | the | 12206 |
NN co-occurrences within the 10 most frequent words are presented in a table.
The graph below gives much more information. Here, the top-1000 words are plotted against each other and the dots indicate NN co-occurrences. The diameter of the dots increases with the significance of the co-occurrence. Both axis are scaled logarithmic to shift the emphasis to the top words.
The picture above is very typical for a language, therefore the name language fingerprint. Comparing these fingerprints for different languages one is able to identify determiners, prepositions etc. by its graphical properties.
Frequency of the most frequent word:
select @maxfreq:=(select freq from words where w_id=101);
Table data:
select w1.word,w2.word,c.freq from co_n c, words w1, words w2 where w1.w_id=w1_id and w2.w_id=w2_id and w1_id>100 and w2_id>100 and 110>=w1_id and 110>=w2_id and c.freq>(select count(*) from sentences)/100000 order by w1.w_id;
Picture data:
select if(12>w1_id-99,w1.word,"-"),if(12>w2_id-99,w2.word,"-"),w1_id-99,w2_id-99,1/(log(c.freq/@maxfreq)*log(c.freq/@maxfreq)/20) from co_n c, words w1, words w2 where w1.w_id=w1_id and w2.w_id=w2_id and w1_id>100 and w2_id>100 and 1100>=w1_id and 1100>=w2_id and c.freq>(select count(*) from sentences)/100000;