New estimation methods of count-min sketch

被引：2
|
作者：
Li, HS [1 ]
Huang, HK [1 ]
机构：
[1] Beijing Jiaotong Univ, Inst Compute Sci & Sci, Sch Comp & Informat Technol, Beijing 100044, Peoples R China
来源：
15TH INTERNATIONAL WORKSHOP ON RESEARCH ISSUES IN DATA ENGINEERING: STREAM DATA MINING AND APPLICATIONS, PROCEEDINGS | 2005年
关键词：
D O I：
10.1109/RIDE.2005.12
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
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.
引用
收藏
页码：73 / 80
页数：8
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