Web prefetching through automatic categorization

The present report provides a novel transparent and speculative algorithm for content based web page prefetching. The proposed algorithm relies on a user profile that is dynamically generated when the user is browsing the Internet and is updated over time. The objective is to reduce the user perceived latency by anticipating future actions. In doing so the adaboost algorithm is used in order to automatically annotate the outbound links of a page to a predefined set of “labels”. Afterwards, the links that correspond to labels relevant to the user’s preferences are pre-fetched in an effort to reduce the perceived latency when the user is surfing the Internet. A comparison between the proposed algorithm against two other pre-fetching algorithms yield improved cache-hit rates given a moderate bandwidth overhead