A Semi-Random Prediction Scenario for User Requests

Since the introduction of the World Wide Web (WWW) at the beginning of the 90s, the Internet community has grown steadily and is now more than 1000 times larger as it was in the beginning. To meet the growing requirements for an easy and efficient information retrieval from the Internet, technologies that allow prediction of user requests are gaining more and more importance. Many approaches exist to predict static HTML pages with Markov Chains, but more general models are needed to depict pure data (such as dynamic HTML) requests adequately. In this paper we present a scenario to model, test and classify user requests that is based upon a controlled strategy, also referred to as semi-random strategy.

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