Altıngövde İsmail ŞengörDemir, EnginCan, FazlıUlusoy, Özgür2016-02-082016-02-082008-07http://hdl.handle.net/11693/26759Date of Conference: 20 - 24 July, 2008Conference name: SIGIR '08 Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrievalWeb search engines typically index and retrieve at the page level. In this study, we investigate a dynamic pruning strategy that allows the query processor to first determine the most promising websites and then proceed with the similarity computations for those pages only within these sites.EnglishCluster-skippingDynamic query pruningInverted indexComputer softwareInformation retrievalInformation servicesQuery processingResearch and development managementSearch enginesWebsitesCluster-skippingDynamic query pruningInverted indexPage levelsPruning strategiesQuery processorsSimilarity computationsWeb search enginesWorld Wide WebConference Paper10.1145/1390334.1390543