Essays about: "Trace Clustering"
Showing result 1 - 5 of 6 essays containing the words Trace Clustering.
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1. Evaluating Process Mining Techniques on PACS Command Usage Data : Exploring common process mining techniques and evaluating their applicability on PACS event log data for domain-specific workflow analysis
University essay from Linköpings universitet/Institutionen för datavetenskapAbstract : Many software companies today collect command usage data by monitoring and logging user interactions within their applications. This is not always utilised to its full potential, but with the use of state-of-the-art process mining techniques, this command usage log data can be used to gain insights about the users' workflows. READ MORE
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2. Intelligence Extraction Using Machine Learning for Threat Identification Purposes : An Overview
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Radar is an invaluable tool for detecting and assessing threats on land, on the seas and in the air. To properly evaluate threats, radar operators construct threat libraries where the signal characteristics of emitters are stored and mapped to specific types of platforms. READ MORE
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3. Comparison of Distance Metrics for Trace Clustering in Process Mining : An Effort to Simplify Analysis of Usage Patterns in PACS
University essay from Linköpings universitet/Programvara och systemAbstract : This study intended to validate if clustering could be used to simplify models generated with process mining. The intention was also to see if these clusters could suggest anything about user efficiency. To that end a new metric where devised, average mean duration deviation. READ MORE
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4. Natural Fingerprinting of Steel
University essay from Luleå tekniska universitet/Institutionen för system- och rymdteknikAbstract : A cornerstone in the industry's ongoing digital revolution, which is sometimes referred to as Industry 4.0, is the ability to trace products not only within the own production line but also throughout the remaining lifetime of the products. READ MORE
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5. AUTOMATIC ANOMALY DETECTION AND ROOT CAUSE ANALYSIS FOR MICROSERVICE CLUSTERS
University essay from Umeå universitet/Institutionen för datavetenskapAbstract : Large microservice clusters deployed in the cloud can be very difficult to both monitor and debug. Monitoring theses clusters is a first step towards detection of anomalies, deviations from normal behaviour. Anomalies are often indicators that a component is failing or is about to fail and should hence be detected as soon as possible. READ MORE