Figure 1. Markov Chain Model&Figure 2. Transition matrix-Study of a Random Navigation on the Web Using Software Simulation

For a good simulation it is very important to find methods for navigating through the web (Levene and Wheeldon, 2004). John Kemeny and Laurie Snell have proposed the use of Markov models for web simulations (Kemeny and Snell, 1960). Cadez et al. (2000) used Markov models for classifying the sessions into different categories for browsers. Some other proposed techniques choose to combine different order Markov models for obtaining low state complexity and improving accuracy, as Deshpande and Karypis (2004). Dongshan and Junyi (2002) used for predicting the access providing good scalability and high coverage a hybrid-order tree-like Markov model. As an alternative to the Markov model Pitkow proposed a longest subsequence model (Pitkow and Pirolli, 1999), also for predicting the next page accessed by the user Sarukkai chose Markov models (Sarukkai, 2000). Transitions are simulated using the Markov Chain nodes, Google matrix and an arbitrary initial probability distribution. Examples can be seen in Figure 1 and Figure 2.https://www.edusoft.ro/brain/index.php/brain/issue/view/3