Procedia Computer Science · 2015 · 11 citations · 8 references
ComputingComputer EngineeringComputer ScienceData MiningMachine LearningWeb AnalyticsCachingCaching StrategiesClassificationDecision TreesWeb MiningWeb Performance OptimizationCache OptimizationCache Replacement PoliciesCache Replacement Policy OptimizationCaching ArchitecturesLog Data AnalysisSliding Window AnalysisWeb Log MiningWeb Proxy Policy
In this paper, we improved the performance of Web proxy cache replacement policies such as LRU and GDSF by adapting a Very Fast Decision Tree learning technique. In the first part, a sliding window method integrated with Very Fast Decision tree classifier (VFDT) to classify the web log data and predict the classes of web objects to be revisited again in future or not. In the second part, a Very Fast Decision Tree classifier is incorporated with proxy caching policies to form novel approaches known as VFDT-LRU and VFDT-GDSF. This proposed approach improves the performances of LRU and GDSF in terms of hit and byte hit ratio respectively.
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