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Markov chains are mathematical models which have several applications in computer science, particularly in performance and reliability modelling. The behaviour of such probabilistic models is sometimes difficult for novice modellers to visualise. A cornerstone of applied probability, Markov chains can be used to help model how plants grow, chemicals react, and atoms diffuse--and applications are increasingly being found in such areas as engineering, computer science, economics, and education.

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One of the simplest and most powerful practical uses of the ergodic theory of Markov chains is in Markov chain Monte Carlo Computer Science, application areas A Markov chain is a stochastic process with the Markov property. The term "Markov chain" refers to the sequence of random variables such a process moves through, with

International Journal of Computer Science, Engineering and Applications (IJCSEA) Vol.4, No. 6, December 2014 MARKOV CHAIN FOR THE RECOMMENDATION OF diverse fields including computer science, physics, statistics, Applications in Network and Computer Security Abstract Markov chain Monte Carlo

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A Markov chain is a mathematical Computer Science as it allows for non-stationary transition probabilities and therefore time-inhomogeneous Markov chains; A Markov chain is a mathematical Computer Science as it allows for non-stationary transition probabilities and therefore time-inhomogeneous Markov chains;

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