This chapter defines a PageRank System for ranks web pages according to
the transit detected in them. This simulation uses Discrete-Time and Continuous-Time Markov Chain Processes. For both approximations, numerical examples of
both conditional probabilities and transition rate rates are provided. While both
models are treated separately, in the end the desirability of designing a mixed network is discussed.
Keywords: Conditional Probabilities, Continuous-Time Markov Chain Process, Discrete-Time Markov Chain Process, Initial State Vector, Markov Chain Process, Steady-State Vector, PageRank System, Row-Vector of Final Conditions, RowVector of Initial Conditions, Transition Matrix
