文章基本信息

标题：Intelligent Web Objects Prediction Approach in Web Proxy Cache Using Supervised Machine Learning and Feature Selection
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作者：Amira Abdalla ; Sarina Sulaiman ; Waleed Ali 等
期刊名称：International Journal of Advances in Soft Computing and Its Applications
印刷版ISSN：2074-8523
出版年度：2015
卷号：7
期号：3
出版社：International Center for Scientific Research and Studies
摘要：Web proxy cache is used to enhance the performance of network by keeping popular web objects in cache of proxy server for closer access. Intelligent approaches aim at improving the performance of conventional strategies. Mostly focus was on improving prediction mechanism, to guess the ideal objects that will be revisited in future; cache them and combine the result with the conventional algorithm. This research proposes an improved prediction method using automated method to select the influence features that produce accurate prediction results before combining with conventional algorithm. The method use supervised machine learning based on Na.ve Bayes (NB) and Decision Tree (C4.5). It applies wrapper feature selection to specify influence features with optimal subset to improve the predictive power. Additionally two more features are extracted to know user's interest to make a smart and a wise decision for caching. The results showed that reduction for the number of features has a good impact on reducing computation time. Moreover, optimal subset selection achieves high performance and enhances accuracy
关键词：Web Object Prediction; Web Proxy Cache; Wrapper Feature ; Selection; Feature Extraction; Supervised Machine Learning