文章基本信息

标题：Web Proxy Cache Content Classification based on Support Vector Machine
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作者：W. Ali ; S.M. Shamsuddin ; A.S. Ismail 等
期刊名称：Journal of Artificial Intelligence
印刷版ISSN：1994-5450
电子版ISSN：2077-2173
出版年度：2011
卷号：4
期号：1
页码：100-109
DOI：10.3923/jai.2011.100.109
出版社：Asian Network for Scientific Information
摘要：Web proxy caching plays a key role in improving the world wide web performance. However, the difficulty in determining which web objects will be re-visited in the future is still a big problem faced by existing web proxy caching techniques. In this study, we present a new approach which depends on the capability of support vector machine to learn from web proxy log data and predict the classes of objects to be re-visited. Therefore, usage of the cache can be optimized efficiently. Experimental results have revealed that the support vector machine produces similar correct classification rate compared to neuro-fuzzy system. However, the support vector machine achieves much better true positive rate and performs much faster than neuro-fuzzy system for both training and testing in several datasets.