About cookies on this site Our websites require some cookies to function properly (required). In addition, other cookies may be used with your consent to analyze site usage, improve the user experience and for advertising. For more information, please review your options. By visiting our website, you agree to our processing of information as described in IBM’sprivacy statement. To provide a smooth navigation, your cookie preferences will be shared across the IBM web domains listed here.
Publication
Annals of Applied Probability
Paper
Random walks with "back buttons"
Abstract
We introduce backoff processes, an idealized stochastic model of browsing on the World Wide Web, which incorporates both hyperlink traversals and use of the "back button." With some probability the next state is generated by a distribution over out-edges from the current state, as in a traditional Markov chain. With the remaining probability, however, the next state is generated by clicking on the back button and returning to the state from which the current state was entered by a "forward step." Repeated clicks on the back button require access to increasingly distant history. We show that this process has fascinating similarities to and differences from Markov chains. In particular, we prove that, like Markov chains, back-off processes always have a limit distribution, and we give algorithms to compute this distribution. Unlike Markov chains, the limit distribution may depend on the start state.