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

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