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Today most of the information in all areas is available over the web. It increases the web utilization as
well as attracts the interest of researchers to improve the effectiveness of web access and web utilization.
As the number of web clients gets increased, the bandwidth sharing is performed that decreases the web
access efficiency. Web page prefetching improves the effectiveness of web access by availing the next
required web page before the user demand. It is an intelligent predictive mining that analyze the user web
access history and predict the next page. In this work, vague improved markov model is presented to
perform the prediction. In this work, vague rules are suggested to perform the pruning at different levels of
markov model. Once the prediction table is generated, the association mining will be implemented to
identify the most effective next page. In this paper, an integrated model is suggested to improve the
prediction accuracy and effectiveness.