用于从事件日志中挖掘模式的数据聚类算法

Proceedings of the 3rd IEEE Workshop on IP Operations & Management (IPOM 2003) (IEEE Cat. No.03EX764) Pub Date : 2003-12-19 DOI:10.1109/IPOM.2003.1251233

Risto Vaarandi

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引用次数: 415

摘要

今天，事件日志包含大量的数据，可以很容易地压倒一个人。因此，从事件日志中挖掘模式是一项重要的系统管理任务。本文提出了一种新的日志文件数据集聚类算法，该算法有助于从日志文件中检测频繁模式，建立日志文件概要，识别异常日志文件行。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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A data clustering algorithm for mining patterns from event logs

Today, event logs contain vast amounts of data that can easily overwhelm a human. Therefore, mining patterns from event logs is an important system management task. The paper presents a novel clustering algorithm for log file data sets which helps one to detect frequent patterns from log files, to build log file profiles, and to identify anomalous log file lines.

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Proceedings of the 3rd IEEE Workshop on IP Operations & Management (IPOM 2003) (IEEE Cat. No.03EX764)

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