Web servers manage large numbe rof documents of widely variable sizes. Moreover, the access patterns on the documents may also c hange over time. While some documents are highly popular over a prolonged period of time, we expe c tnewly added documents to increase in popularity while demand for most older documents decreases. It is therefore important to design e ective caching strategy at the web server. In this paper, we present our approach to the problem. Our main contribution lies in the design of a novel prefetching strategy, called RAP. RAP identi es a set of association rules from the Web server's access log. Unlike existing mining strategy, RAP's miner values recently added log records more than earlier log records. Based on the rules, RAP predicts and prefetches documents from users initial requests. We conducted extensive study to evaluate RAP. The results show that RAP signi cantly outperforms existing schemes. We also show that the mining and caching cost is relatively low.

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The COntext INterchange (COIN) strategy is an approach to solving the problem of interoperability of semantically heterogeneous data sources through context mediation. COIN has used its own notation and syntax for representing ontologies. More recently, the OWL Web Ontology Language is becoming established as the W3C recommended ontology language. We propose the use of the COIN strategy to solve context disparity and ontology interoperability problems in the emerging Semantic Webboth at the ontology level and at the data level. In conjunction with this, we propose a version of the COIN ontology model that uses OWL and the emerging rules interchange language, RuleML.