Analyzing User

There is currently great interest in building information mediators that can integrate information from multiple data sources such as database systems or Web sources. An issue in building information mediators is how to make them responsive given the high response time for retrieving data from the data sources being integrated, which are databases or Web servers residing remotely. We present an approach for optimizing the performance of information mediators by selectively materializing data. We rst present our overall framework for materialization in a mediator environment. We then stress the need to materialize data selectively and outline the factors that must be considered to select data to materialize. We present an algorithm for identifying classes of data to materialize by analyzing one of the factors which is the distribution of user queries. We present results with an implemented version of our optimization system for the Ariadne information mediator which show signiicant performance improvement over no materialization and existing schemes such as page level caching.