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A comment on Markov Chains Explained.

Re:Markov Chains Explained by jlukecarlson on Saturday July 05, 2014 @05:37PM (#7993041)
Interesting article, would have been helpful when I was writing a paper on Google PageRank since it is a markov chain. I do think it would be valuable to talk about equilibrium distributions and how you can determine the tendency of the system
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Re:Markov Chains Explained by cpeterso on Saturday July 05, 2014 @07:30PM (#7993298)
How does PageRank use Markov Chains? That's an interesting idea.
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Re:Markov Chains Explained by pedrosorio on Saturday July 05, 2014 @08:29PM (#7993401)
It models the web as a Markov Chain where web pages are states and the transitions are the outgoing links.
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Re:Markov Chains Explained by jlukecarlson on Saturday July 05, 2014 @11:11PM (#7993709)
Exactly and the actual page rank of the site comes from finding the equilibrium distribution from the transition matrix, which in this case is called a Google matrix.
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