{"title":"New estimation methods of Count-Min sketch","authors":"Hongsong Li, Houkuan Huang","doi":"10.1109/RIDE.2005.12","DOIUrl":null,"url":null,"abstract":"Count-Min sketch is an efficient approximate query tool for data stream. In this paper we address how to further improve its point query performance. Firstly, we modify the estimation method under cash register model. Our method will relieve error propagation. Secondly, we find better method under turnstile model and prove that our method is more efficient than that Count-Min sketch. These conclusions are well supported by experimental results.","PeriodicalId":404914,"journal":{"name":"15th International Workshop on Research Issues in Data Engineering: Stream Data Mining and Applications (RIDE-SDMA'05)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"15th International Workshop on Research Issues in Data Engineering: Stream Data Mining and Applications (RIDE-SDMA'05)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RIDE.2005.12","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Count-Min sketch is an efficient approximate query tool for data stream. In this paper we address how to further improve its point query performance. Firstly, we modify the estimation method under cash register model. Our method will relieve error propagation. Secondly, we find better method under turnstile model and prove that our method is more efficient than that Count-Min sketch. These conclusions are well supported by experimental results.