Mining Logs for Long-Term Patterns

被引：0

作者：

Novikov, Boris ^{[1
]}

Michailova, Elena ^{[1
]}

Vasilik, Dmitri ^{[1
]}

Ivannikova, Ekaterina ^{[1
]}

Pigul, Alice ^{[1
]}

机构：

[1] St Petersburg State Univ, St Petersburg 199034, Russia

来源：

DATABASES AND INFORMATION SYSTEMS VII | 2013年 / 249卷

关键词：

Pattern mining; log mining; period detection; PARTIAL PERIODIC PATTERNS;

D O I：

10.3233/978-1-61499-161-8-57

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The discovery of high-level long-term system behavior patterns is essential for several tasks such as system analysis, performance tuning, adaptive data placement in a cloud data centers. This paper describes techniques for mining long-term activities from database query logs. We describe algorithms for extraction of query groups with similar occurrence patterns, identification of periodic groups, and experimentally evaluate the correspondence of the query groups with business processes in the system.

引用

页码：57 / 70

页数：14

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