Problem Classification Method to enhance the ITIL Incident, Problem and Change Management Process

Problem determination and resolution PDR is the process of detecting anomalies in a monitored system, locating the problems responsible for the issue, determining the root cause and fixing the cause of the problem. The cost of PDR represents a substantial part of operational costs, and faster, more effective PDR can contribute to a substantial reduction in system administration costs. In this paper, we propose to automate the process of PDR by leveraging machine learning methods. The main focus is to effectively categorize the problem a user experiences by recognizing the problem specificity leveraging all available training data such like the performance data and the logs data. Specifically, we transform the structure of the problem into a hierarchy which can be determined by existing taxonomy in advance. We then propose an efficient hierarchical incremental learning algorithm which is capable of adjusting its internal local classifier parameters in real-time. Comparing to the traditional batch learning algorithms, this online learning framework can significantly decrease the computational complexity of the training process by learning from new instances on an incremental fashion. In the same time this reduces the amount of memory required to store the training instances. We demonstrate the efficiency of our approach by learning hierarchical problem patterns for several issues occurred in distributed web applications. Experimental shows that our approach substantially outperforms previous methods.

By: Yang Song; Anca Sailer; Hidayatullah Shaikh

Published in: RC24847 in 2009


This Research Report is available. This report has been submitted for publication outside of IBM and will probably be copyrighted if accepted for publication. It has been issued as a Research Report for early dissemination of its contents. In view of the transfer of copyright to the outside publisher, its distribution outside of IBM prior to publication should be limited to peer communications and specific requests. After outside publication, requests should be filled only by reprints or legally obtained copies of the article (e.g., payment of royalties). I have read and understand this notice and am a member of the scientific community outside or inside of IBM seeking a single copy only.


Questions about this service can be mailed to .