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Web Proxy Cache Content Classification based on Support Vector Machine

Author(s): W. Ali | S.M. Shamsuddin | A.S. Ismail

Journal: Journal of Artificial Intelligence
ISSN 1994-5450

Volume: 4;
Issue: 1;
Start page: 100;
Date: 2011;
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Keywords: proxy server | logs file | classification | support vector machine | Web caching

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.
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