NDLI: Machine Learning Methodology for Enhancing Automated Process in IT Incident Management

Content Provider	IEEE Xplore Digital Library
Author	Haochen Li Zhiqiang Zhan
Copyright Year	2012
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.
Starting Page	191
Ending Page	194
File Size	250194
Page Count	4
File Format	PDF
ISBN	9781467322140
DOI	10.1109/NCA.2012.28
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-08-23
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Machine learning Accuracy Training Biological neural networks Computer architecture Optimization data mining IT incident management tokenize neural network numerical optimization
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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