Abstract
Accurately predicting Web user access behavior can minimize user-perceived latency, which is crucial in the rapidly growing World Wide Web. Although traditional Markov models have helped predict user access behavior, they have serious limitations. Hybrid-order treelike Markov models predict Web access precisely while providing high coverage and scalability.
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