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Yang et al., 2020 - Google Patents

Analysing business process anomalies using discrete-time markov chains

Yang et al., 2020

View PDF
Document ID
7111453509967375329
Author
Yang L
McClean S
Donnelly M
Khan K
Burke K
Publication year
Publication venue
2020 IEEE 22nd International Conference on High Performance Computing and Communications; IEEE 18th International Conference on Smart City; IEEE 6th International Conference on Data Science and Systems (HPCC/SmartCity/DSS)

External Links

Snippet

Within a business context, anomalies can be viewed as indicators for inefficiencies or fraud, which impact upon product quality and customer satisfaction. The development of approaches to monitor, detect and predict anomalous business processes remains an …
Continue reading at scholar.archive.org (PDF) (other versions)

Classifications

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    • G06K9/6267Classification techniques
    • G06K9/6279Classification techniques relating to the number of classes
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
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    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/30Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
    • G06F19/34Computer-assisted medical diagnosis or treatment, e.g. computerised prescription or delivery of medication or diets, computerised local control of medical devices, medical expert systems or telemedicine
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