Title :
Bussiness-driven automatic IT change management based on machine learning
Author :
Li, Haochen ; Zhan, Zhiqiang
Author_Institution :
State Key Lab. of Networking & Switching, Beijing Univ. of Posts & Telecommun., Beijing, China
Abstract :
Growing complexity of customer needs is one of the prevailing problems faced by IT enterprises at present, leading to increasingly complex IT service management systems. At the same time, quick response to unexpected problems and externally imposed requirements are testing the IT change management. In order to solve the problems mentioned above and satisfy the customer needs timely, we consider automating the change management process with business-driven perspective so as to reduce the service interruption time and cost brings by changes. This paper proposes a solution for automation of the whole change management process and also assesses and validates the change solution we selected.
Keywords :
customer satisfaction; learning (artificial intelligence); management of change; IT enterprise; IT service management system; business-driven perspective; bussiness-driven automatic IT change management; change solution; customer need; information technology; machine learning; service interruption cost; service interruption time; Accuracy; Biological neural networks; Business; Data mining; Machine learning; Training; IT change management; data mining; neural network; numerical optimization; text mining;
Conference_Titel :
Network Operations and Management Symposium (NOMS), 2012 IEEE
Conference_Location :
Maui, HI
Print_ISBN :
978-1-4673-0267-8
Electronic_ISBN :
1542-1201
DOI :
10.1109/NOMS.2012.6212078
