Cost Model for the Recommendation of Materialized Webviews

In this paper we present a cost model for the recommendation of candidate webviews. Our idea is tointervene at regular period of time in order to filter the candidate webviews which will be used by analgorithm for the selection of materialized webviews in data–intensive websites (DIWS). The aim is toreduce the complexity and the execution cost of the online selection of materialized webviews. A webview isa static instance of a dynamic web page. The materialization of webviews consists of storing the results ofsome requests on the server in order to avoid repetitive data generation from the sources. Our experimentresults show that our solution is very efficient to specify the more profitable webviews and to improve thequery response time.