C4.5: programs for machine learning
C4.5: programs for machine learning
On the Optimality of the Simple Bayesian Classifier under Zero-One Loss
Machine Learning - Special issue on learning with probabilistic representations
Pattern Recognition and Machine Learning (Information Science and Statistics)
Pattern Recognition and Machine Learning (Information Science and Statistics)
Efficient ticket routing by resolution sequence mining
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
SOAR: SOcially Aware Routing for Request Matching in Enterprise Environments
SCC '08 Proceedings of the 2008 IEEE International Conference on Services Computing - Volume 2
Who do you call? problem resolution through social compute units
ICSOC'12 Proceedings of the 10th international conference on Service-Oriented Computing
Scheduling service tickets in shared delivery
ICSOC'12 Proceedings of the 10th international conference on Service-Oriented Computing
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In many network and IT (information technology) systems, users submit loosely defined (or "fuzzy") requests to obtain answers, solutions, or resources. Fuzzy requests are often presented in problem tickets and processed by an IT service management system. In such a system, problems are typically reported using vague user-generated descriptions of the symptoms (e.g., "my e-mail is not working"). Making use of the reported symptoms, the incident management system is then responsible for identifying the component causing the problem. An accurate and quick diagnosis from the fuzzy symptoms becomes critical for an efficient and timely resolution of the problem. In this paper, we propose a system for automated incident management using historical information (AIM-HI), a framework for autonomous routing of requests in large-scale IT global service delivery. AIM-HI incorporates historical request resolution information and frequency, together with queue bouncing trends to extrapolate algorithms for streamlining and automating the dispatch of requests or work among support groups and IT specialists. The simplicity and scalability of AIM-HI should lead to deployment in actual real operational systems in the future.