{"title":"Strategies for parallel data mining","authors":"D. Skillicorn","doi":"10.1109/4434.806976","DOIUrl":null,"url":null,"abstract":"This article presents a set of cost measures that can be applied to parallel algorithms to predict their computation, data access and communication performance. These measures make it possible to compare different parallel implementation strategies for data mining techniques without benchmarking each one.","PeriodicalId":282630,"journal":{"name":"IEEE Concurr.","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1999-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"72","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Concurr.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/4434.806976","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 72
Abstract
This article presents a set of cost measures that can be applied to parallel algorithms to predict their computation, data access and communication performance. These measures make it possible to compare different parallel implementation strategies for data mining techniques without benchmarking each one.
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