A vector space model for automatic indexing
Communications of the ACM
Ensembles of Models for Automated Diagnosis of System Performance Problems
DSN '05 Proceedings of the 2005 International Conference on Dependable Systems and Networks
Pattern Recognition and Machine Learning (Information Science and Statistics)
Pattern Recognition and Machine Learning (Information Science and Statistics)
A service delivery platform for server management services
IBM Journal of Research and Development
How to reuse a faceted classification and put it on the semantic web
ISWC'10 Proceedings of the 9th international semantic web conference on The semantic web - Volume Part I
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IT incident management aims to maintain high levels of service quality and availability by restoring normal service operations as quickly as possible and minimizing business impact. Enterprises often maintain many applications to support their business. It is a significant challenge to diagnose incidents at application level due to complicated causes often aggregated from the shared IT environment, network, hardware, software, and changes. In this paper, we present a new approach to diagnosing application incidents by effectively searching for relevant co-occurring and reoccurring incidents. These relevant incidents reveal patterns of application failures and provide insights into incident resolution and prevention. This paper also provides a case study where we implement this approach and evaluate its performance in terms of search accuracy.