Improving the Performance of Proxy Server by Using Data Mining Technique
Creators
Description
Currently, web usage make a huge data from a lot of
user attention. In general, proxy server is a system to support web
usage from user and can manage system by using hit rates. This
research tries to improve hit rates in proxy system by applying data
mining technique. The data set are collected from proxy servers in the
university and are investigated relationship based on several features.
The model is used to predict the future access websites. Association
rule technique is applied to get the relation among Date, Time, Main
Group web, Sub Group web, and Domain name for created model.
The results showed that this technique can predict web content for the
next day, moreover the future accesses of websites increased from
38.15% to 85.57 %.
This model can predict web page access which tends to increase
the efficient of proxy servers as a result. In additional, the
performance of internet access will be improved and help to reduce
traffic in networks.
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Additional details
References
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