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A New Markov Model For Web Access Prediction
November/December 2002 (vol. 4 no. 6)
pp. 34-39
Xing Dongshan, Xi?an Jiaotong University
Shen Junyi, Xi?an Jiaotong University

Web access prediction is an important research direction in Web mining. Markov models are well-suited for predicting Web access. Although higher-order Markov models have good predictions result, these models have several limitations associated with high state-space complexity and reduced coverage. These affect the prediction performance deeply. A new Web access prediction model, Hybrid-order Tree-like Markov Model (HTMM), is proposed in this article. The technique intelligently merges two methods: a tree-like Markov model method that aggregates the access sequences by pattern matching and a hybrid-order method that combines varying order Markov models so that the resulting model has a low state complexity, improved prediction accuracy, and retains high coverage. Experiments confirm its usefulness. It's suitable for applications in E-business, such as Web prefetching, link prediction, and recommendation.

Index Terms:
Markov model; hybrid order; access prediction; Web mining; E-business
Citation:
Xing Dongshan, Shen Junyi, "A New Markov Model For Web Access Prediction," Computing in Science and Engineering, vol. 4, no. 6, pp. 34-39, Nov.-Dec. 2002, doi:10.1109/MCISE.2002.1046594
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