Approximate Frequent Pattern Discovery Over Data Stream

被引：0

作者：

Kerdprasop, Kittisak ^{[1
]}

Kerdprasop, Nittaya ^{[1
]}

机构：

[1] Suranaree Univ Technol, DEKD Res Unit, Sch Comp Engn, 111 Univ Ave, Nakhon Ratchasima 30000, Thailand

来源：

PROCEEDINGS OF WORLD ACADEMY OF SCIENCE, ENGINEERING AND TECHNOLOGY, VOL 26, PARTS 1 AND 2, DECEMBER 2007 | 2007年 / 26卷

关键词：

Frequent pattern discovery; Approximate algorithm; Data stream analysis;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

Frequent pattern discovery over data stream is a hard problem because a continuously generated nature of stream does not allow a revisit on each data element. Furthermore, pattern discovery process must be fast to produce timely. results. Based on these requirements, we propose an approximate approach to tackle the problem of discovering frequent patterns over continuous stream. Our approximation algorithm is intended to be applied to process a stream prior to the pattern discovery process. The results of approximate frequent pattern discovery have been reported in the paper.

引用

下载

页码：478 / +

页数：2

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