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A Survey on Web Page Prediction and Prefetching Models

机译:网页预测和预取模型的调查

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this paper performs a survey on Web Page Prediction and Prefetching Methods. Prediction and Prefetching methods of Web page have been widely used to reduce the access latency problem on the networks. If Prediction and Prefetching of Web page are not accurate and Prefetched web pages are not visited by the users in their accesses, which mean it is totally wastage of time and bandwidth of network. The limited bandwidth of network and services of server will not be used efficiently and may face the access delay problem. That’s why we need effective and relevant methods for Prediction and Prefetching of Webpage. Markov models, Associations rule mining, NGrams, Clustering and ARM are used widely for predicting the next Webpage. For Prefetching, we have Prefetching only and Prefetching with caching methods for reducing of the Web access. For the both purpose, log file plays a crucial role. Prediction with Prefetching of Webpage gives a good result for reducing the latency over network of Web access.
机译:本文对网页预测和预取方法进行了调查。网页的预测和预取方法已被广泛用于减少网络上的访问延迟问题。如果网页的预测和预取不准确,并且用户在访问中没有访问预取的网页,则意味着这完全浪费了时间和网络带宽。有限的网络带宽和服务器的服务将无法有效利用,并可能面临访问延迟的问题。因此,我们需要有效且相关的方法来进行网页的预测和预取。马尔可夫模型,关联规则挖掘,NGram,集群和ARM被广泛用于预测下一个网页。对于预取,我们只有预取和使用缓存方法进行预取以减少Web访问。出于这两个目的,日志文件起着至关重要的作用。通过预取网页进行预测可以很好地减少Web访问网络上的延迟。

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