Related papers: Discovering Process Maps from Event Streams
Stream processing is a compute paradigm that promises safe and efficient parallelism. Modern big-data problems are often well suited for stream processing's throughput-oriented nature. Realization of efficient stream processing requires…
Business processes are prone to unexpected changes, as process workers may suddenly or gradually start executing a process differently in order to adjust to changes in workload, season, or other external factors. Early detection of business…
In the last few years there has been a growing interest in Human Activity Recognition~(HAR) topic. Sensor-based HAR approaches, in particular, has been gaining more popularity owing to their privacy preserving nature. Furthermore, due to…
Process mining has matured as analysis instrument for process-oriented data in recent years. Manufacturing is a challenging domain that craves for process-oriented technologies to address digitalization challenges. We found that process…
Process mining is moving beyond mining traditional event logs and nowadays includes, for example, data sourced from sensors in the Internet of Things (IoT). The volume and velocity of data generated by such sensors makes it increasingly…
Monitoring and analyzing process traces is a critical task for modern companies and organizations. In scenarios where there is a gap between trace events and reference business activities, this entails an interpretation problem, amounting…
Given a stream of entries over time in a multi-dimensional data setting where concept drift is present, how can we detect anomalous activities? Most of the existing unsupervised anomaly detection approaches seek to detect anomalous events…
This paper introduces the concept of plant model generation from the recorded traces of events using the process mining technique. The event logs are obtained by visually simulating a simple distributed manufacturing system using the OPC UA…
AI Planning, Machine Learning and Process Mining have so far developed into separate research fields. At the same time, many interesting concepts and insights have been gained at the intersection of these areas in recent years. For example,…
Machine-learning based generation of process models from natural language text process descriptions provides a solution for the time-intensive and expensive process discovery phase. Many organizations have to carry out this phase, before…
Much time in process mining projects is spent on finding and understanding data sources and extracting the event data needed. As a result, only a fraction of time is spent actually applying techniques to discover, control and predict the…
While several techniques for detecting trace-level anomalies in event logs in offline settings have appeared recently in the literature, such techniques are currently lacking for online settings. Event log anomaly detection in online…
Process mining traditionally assumes centralized event data collection and analysis. However, modern Industrial Internet of Things systems increasingly operate over distributed, resource-constrained edge-cloud infrastructures. This paper…
In modern advanced emergency management systems many solutions for decision support have been provided as attempts to support humans to take important decisions for the critical situations recovery. The critical situation detection is a…
Audit trails are evidential indications of activities performers in any logs. Modern reactive systems such as transaction processing systems, management information systems, decision support systems and even executive management systems log…
The rapid growth of Cloud Computing and Internet of Things (IoT) has significantly increased the interconnection of computational resources, creating an environment where malicious software (malware) can spread rapidly. To address this…
Predictive business process monitoring focuses on predicting future characteristics of a running process using event logs. The foresight into process execution promises great potentials for efficient operations, better resource management,…
Numerous process discovery techniques exist for generating process models that describe recorded executions of business processes. The models are meant to generalize executions into human-understandable modeling patterns, notably…
Event collections are frequently built by crawling the live web on the basis of seed URIs nominated by human experts. Focused web crawling is a technique where the crawler is guided by reference content pertaining to the event. Given the…
Due to recent advances in data collection techniques, massive amounts of data are being collected at an extremely fast pace. Also, these data are potentially unbounded. Boundless streams of data collected from sensors, equipments, and other…