Web-log mining for predictive Web caching

Caching is a well-known strategy for improving the performance of Web-based systems. The heart of a caching system is its page replacement policy, which selects the pages to be replaced in a cache when a request arrives. In this paper, we present a Web-log mining method for caching Web objects and use this algorithm to enhance the performance of Web caching systems. In our approach, we develop an n-gram-based prediction algorithm that can predict future Web requests. The prediction model is then used to extend the well-known GDSF caching policy. We empirically show that the system performance is improved using the predictive-caching approach.