Abstract
IT-operational risk management consists of identifying, assessing, monitoring and mitigating the adverse risks of loss resulting from hardware and software system failures. We present a case study in IT-operational risk measurement in the context of a network of Private Branch eXchanges (PBXs). The approach relies on preprocessing and data mining tasks for the extraction of sequential patterns and their exploitation in the definition of a measure called expected risk.
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Grossi, V., Romei, A., Ruggieri, S. (2008). A Case Study in Sequential Pattern Mining for IT-Operational Risk. In: Daelemans, W., Goethals, B., Morik, K. (eds) Machine Learning and Knowledge Discovery in Databases. ECML PKDD 2008. Lecture Notes in Computer Science(), vol 5211. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87479-9_46
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DOI: https://doi.org/10.1007/978-3-540-87479-9_46
Publisher Name: Springer, Berlin, Heidelberg
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