Re: YOU ALL SUCK!
From: Ian Sedwell (ian.sedwell_at_btclick.com)
Date: 09/10/04
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Date: Fri, 10 Sep 2004 16:15:53 +0000 (UTC)
On 2004/09/10 01:05, in article
Xns955FCC8E99C10RepublicPicturesLtd@216.221.81.119, "Tris Orendorff"
<triso@remove-me.cogeco.ca> wrote:
> carl.scharenberg@gmail.com (Carl Scharenberg) wrote in
> news:e930c085.0409020529.2db830fc@posting.google.com:
>
>
>>> This seems to be of somewhat better quality than the output of the
>>> typical random-text generator. Can anyone suggest something on CPAN
>>> useful for such?
>>
>> You can do this by analyzing a sample text at a higher level. Instead
>> of generating text from the frequency of single letters, you generate
>> using the frequencies of 2, 3, or 4-letter sequences. You analyze a
>> large text so you have a database of frequencies. When generating each
>> new character you look at the frequences of the letters given that the
>> 3 previous letters are 'the'. The possibilities are a space, 'r'
>> (their), 'y' (they), and some others. Overall it will generate words
>> and even phrases that seem to almost make sense. It is neat stuff.
>
> This is known as a Markov Chain and it works even better if you generate using
> words rather than letters.
> Using letters creates words and non words. The output is written in the same
> style as the input text.
>
There's a technique for verifying the authorship of a text by comparing the
frequency of triples in a text of known provenance against the frequency of
the same triples in the suspect text. The larger the texts, the better the
accuracy. Presumably, if one sampled a large enough corpus from a single
author, one could generate a Markov Chain in the style of that author.
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