Generating random text: a Markov chain algorithm
Based on the program presented in the "Design and Implementation" chapter of The Practice of Programming (Kernighan and Pike, Addison-Wesley 1999). See also Computer Recreations, Scientific American 260, 122 - 125 (1989).
A Markov chain algorithm generates text by creating a statistical model of potential textual suffixes for a given prefix. Consider this text:
I am not a number! I am a free man!
Our Markov chain algorithm would arrange this text into this set of prefixes and suffixes, or "chain": (This table assumes a prefix length of two words.)
Prefix Suffix "" "" I "" I am I am a I am not a free man! am a free am not a a number! I number! I am not a number!
To generate text using this table we select an initial prefix ("I am", for example), choose one of the suffixes associated with that prefix at random with probability determined by the input statistics ("a"), and then create a new prefix by removing the first word from the prefix and appending the suffix (making the new prefix is "am a"). Repeat this process until we can't find any suffixes for the current prefix or we exceed the word limit. (The word limit is necessary as the chain table may contain cycles.)
Our version of this program reads text from standard input, parsing it into a Markov chain, and writes generated text to standard output. The prefix and output lengths can be specified using the -prefix and -words flags on the command-line.