{"title":"并行数据挖掘策略","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":"{\"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}","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}
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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