SCIS Event

Dissertation Proposal Defense

Large Scale Data Mining for IT Service Management

Date / Time:

Apr. 21, 2016 @ 09:00 am


Florida International University
ECS: 243


Chunqiu Zeng
Florida International University

Chunqiu Zeng


More than ever, Business heavily rely on IT service delivery to meet their current and frequently changing business requirements. Optimizing the quality of service delivery improves customer satisfaction and continues to be a critical driver for business growth. The routine maintenance procedure plays a key function in IT service management, which typically gets involved with problem detection, determination and resolution for the service infrastructure. Problem detection in IT environment is realized by the system monitoring. The system monitoring is capable of tracking the states of a system by collecting system performance statistics and generating incident events. All the generated events are consolidated in the enterprise console. The enterprise console analyzes the events and makes the decision to report an IT problem with a service ticket. According to the incident ticket, combined with both the system performance statistics and event data, problem diagnosis and resolution are conducted. From the perspective of data mining, three research directions are identified and considered to be helpful for IT service management optimization: (1) Automatically determine problem categories according to the symptom description in a ticket; (2) Intelligently discover interesting temporal patterns from system events; (3) Instantly identify temporal dependencies among system performance statistics data. Provided with ticket, event, and system performance statistics data, the three directions can be effectively addressed with a data-driven solution. The quality of IT service delivery can be improved in an efficient and effective way. I propose to address the research topics outlined above. Concretely, I will focus on designing and developing data-driven solutions to help system administrators better manage the system and alleviate the human efforts involved in IT Service management in my dissertation.


Chunqiu Zeng is currently a PhD candidate in Computer Science of Florida International University. He is advised by Dr. Tao Li. His research interests mainly focus on Distributed Data Mining, Temporal Data Mining, Event Mining. He received his Bachelor's and Master's degrees both in Computer Science at Sichuan University in China. During his PhD study, he did one summer internship at IBM T.J. Watson Research Center in 2013 and two summer internships at Google in 2014 and 2015 respectively.