Related papers: Data-Enhanced Process Models in Process Mining

The exploding growth of digital data in the information era and its immeasurable potential value has called for different types of data-driven techniques to exploit its value for further applications. Information visualization and data…

Process discovery aims to discover descriptive process models from event logs. These discovered process models depict the actual execution of a process and serve as a foundational element for conformance checking, performance analyses, and…

Major domains such as logistics, healthcare, and smart cities increasingly rely on sensor technologies and distributed infrastructures to monitor complex processes in real time. These developments are transforming the data landscape from…

Process mining provides methods to analyse event logs generated by information systems during the execution of processes. It thereby supports the design, validation, and execution of processes in domains ranging from healthcare, through…

The current information age has increasingly required organizations to become data-driven. However, analyzing and managing raw data is still a challenging part of the data mining process. Even though we can find interview studies proposing…

Process mining is a discipline which concerns the analysis of execution data of operational processes, the extraction of models from event data, the measurement of the conformance between event data and normative models, and the enhancement…

Process mining has grown popular today given their ability to provide managers with insights into the actual business process as executed by employees. Process mining depends on event logs found in process aware information systems to model…

Process mining is a field of computer science that deals with discovery and analysis of process models based on automatically generated event logs. Currently, many companies use this technology for optimization and improving their…

Process mining is the common name for a range of methods and approaches aimed at analysing and improving processes. Specifically, methods that aim to derive process models from event logs fall under the category of process discovery. Within…

Process mining has emerged as a way to analyze the behavior of an organization by extracting knowledge from event logs and by offering techniques to discover, monitor and enhance real processes. In the discovery of process models,…

Process mining is a research field focused on the analysis of event data with the aim of extracting insights in processes. Applying process mining techniques on data from smart home environments has the potential to provide valuable…

Process mining has gained traction over the past decade and an impressive body of research has resulted in the introduction of a variety of process mining approaches measuring process performance. Having this set of techniques available,…

Modern information systems are able to collect event data in the form of event logs. Process mining techniques allow to discover a model from event data, to check the conformance of an event log against a reference model, and to perform…

Process-mining techniques have emerged as powerful tools for analyzing event data to gain insights into business processes. In this paper, we present a comprehensive analysis of road traffic fine management processes using the pm4py library…

The application of process mining for unstructured data might significantly elevate novel insights into disciplines where unstructured data is a common data format. To efficiently analyze unstructured data by process mining and to convey…

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…

Process mining methods often analyze processes in terms of the individual end-to-end process runs. Process behavior, however, may materialize as a general state of many involved process components, which can not be captured by looking at…

Automated process discovery from event logs is a key component of process mining, allowing companies to acquire meaningful insights into their business processes. Despite significant research, present methods struggle to balance important…

The number of events recorded for operational processes is growing every year. This applies to all domains: from health care and e-government to production and maintenance. Event data are a valuable source of information for organizations…

The discipline of process mining deals with analyzing execution data of operational processes, extracting models from event data, checking the conformance between event data and normative models, and enhancing all aspects of processes.…