NDLI: Intelligent Web Objects Prediction Approach in Web Proxy Cache Using Supervised Machine Learning and Feature Selection

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Intelligent Web Objects Prediction Approach in Web Proxy Cache Using Supervised Machine Learning and Feature Selection

Content Provider	Semantic Scholar
Author	Abdalla, Amira Sulaiman, Sarina Ali, Waleed
Copyright Year	2015
Abstract	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 Naive 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.
Starting Page	146
Ending Page	164
Page Count	19
File Format	PDF HTM / HTML
Volume Number	7
Alternate Webpage(s)	http://home.ijasca.com/data/documents/11IJASCA-070311_Pg146-164_Intelligent-Web-Objects-Prediction-Approach.pdf
Journal	SOCO 2015
Language	English
Access Restriction	Open
Content Type	Text
Resource Type	Article

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