Machine Learning Methodology for Enhancing Automated Process in IT Incident Management

Haochen Li, Zhiqiang Zhan
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引用次数: 4

Abstract

Operating system experienced a rise in number of incidents in recent years. Analysis and reemployment of past solution therefore may make a contribution in reducing service interrupt time and minimizing business losses. The training and retaining of human resources is another primary disbursement source for enterprise. Thus, it is of great significance for enterprises to find reasonable solutions automatically. Combined with keyword tokenization, data mining, numerical optimization and neural network, this paper presents a system that compares and finds the most similar incident solution in the past, based on the description provided by customers in natural language. We try to improve the automated process by increasing the efficiency and accuracy through machine learning methodology and also devote to presenting a practical decision support method.
增强IT事件管理自动化过程的机器学习方法
近年来,操作系统的攻击事件不断增多。因此,分析和再利用过去的解决方案可以减少业务中断时间,最大限度地减少业务损失。培训和留住人力资源是企业的另一个主要支出来源。因此,企业自动找到合理的解决方案具有重要意义。结合关键词标记化、数据挖掘、数值优化和神经网络等技术,提出了一种基于客户提供的自然语言描述,比较并找出最相似的过去事件解决方案的系统。我们试图通过机器学习方法提高自动化过程的效率和准确性,并致力于提出一种实用的决策支持方法。
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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