While it is just another library I found crap.l to be readable and easy to learn about basic Markov chaining from, picolisp.com/wiki/?ticker .
Implementation usually goes something like this. The math behind it is basically a frequence calculation of how common it is for each word to be followed by another, then when you build your strings you use this probability estimate to choose what words to chain to one you picked (pseudo-) randomly as a kind of seed.
(googlebot seems to have kept up the indexing the ticker since the writing of that article, today it has crawled and cached thousands of pages)
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While it is just another library I found crap.l to be readable and easy to learn about basic Markov chaining from, picolisp.com/wiki/?ticker .
Implementation usually goes something like this. The math behind it is basically a frequence calculation of how common it is for each word to be followed by another, then when you build your strings you use this probability estimate to choose what words to chain to one you picked (pseudo-) randomly as a kind of seed.
(googlebot seems to have kept up the indexing the ticker since the writing of that article, today it has crawled and cached thousands of pages)