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iLSE: An Intelligent Web-Based System for Log Structuring and Extraction

机译:iLSE:基于智能Web的日志结构和提取系统

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Analysing software log files has become a challenging task due to the diversity in file structure and the nonstandardisation of log syntax. During the process of extracting log data, it is required to manually decode the log syntax and interpret data semantics, which can become tedious and is often error-prone if not performed carefully. Contemporary log analysis software tools do exist in the market and most of them offer numerous options to analyse log files, however, their sheer focus is on providing log management solutions instead of log analysis capabilities. In particular, none of them offers a generic parsing and extracting solution that can discover hidden data structures, a critical and effortful task in log analysis. We thereby devise such a solution that is able to automatically identify hidden patterns in a given log file and extract useful information by generalising the patterns. The solution is implemented as an intelligent Web-based system known as iLSE (intelligent Log Structuring and Extraction) whose users are not required to possess fluent programming skills. This paper presents a reference architecture for the system as well as a comparison study on how the system performs against contemporary log analysis systems.
机译:由于文件结构的多样性和日志语法的非标准化,分析软件日志文件已成为一项具有挑战性的任务。在提取日志数据的过程中,需要手动解码日志语法并解释数据语义,这可能变得乏味并且如果不仔细执行通常会容易出错。市场上确实存在当代的日志分析软件工具,其中大多数提供了许多分析日志文件的选项,但是,其纯粹的重点是提供日志管理解决方案而不是日志分析功能。特别是,它们都没有提供可以发现隐藏数据结构的通用解析和提取解决方案,这是日志分析中一项艰巨而艰巨的任务。因此,我们设计了一种解决方案,该解决方案能够自动识别给定日志文件中的隐藏模式并通过概括模式来提取有用的信息。该解决方案实现为称为iLSE(智能日志结构和提取)的基于Web的智能系统,不需要用户具备流利的编程技能。本文介绍了该系统的参考架构,以及该系统与现代日志分析系统的性能比较研究。

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