This paper presents a popularity-based selective Markov prefetching model for predicting the forthcoming Web pages. We make use of teh Zipf's law to model the ...
A popularity-based selective Markov prefetching model is presented that can achieve a good hit ratio with reducing the traffic load to some degree and makes ...
This paper presents a popularity-based selective Markov prefetching model for predicting the forthcoming Web pages. We make use of teh Zipf's law to model the ...
A variation of the prediction by partial match model, for example, makes prefetching decisions by reviewing URLs clients have accessed on a particular ...
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In this article, we present different techniques for intelligently selecting parts of different order Markov models so that the resulting model has a reduced ...
The accuracy of low order Markov model is normally not satisfactory. Therefore, we use popularity and similarity-based page rank algorithm to make prediction ...
(PDF) Using Markov Model and Popularity and Similarity-based ...
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Markov models are commonly used in the prediction of the next page access based on the previously accessed pages. Then, we use popularity and similarity based- ...
Nov 14, 2023 · However, it is also based on statistical analysis. A Markov chain is a common and fairly simple way to model random events. It is used in a ...
Nov 21, 2024 · Of the different variations of Markov models, it is generally found that higher-order Markov models display high predictive accuracies on Web ...
Markov models have been widely used for modelling users' web navigation behaviour. In previous work we have presented a dynamic clustering-based Markov ...