Related papers: Process Mining for Python (PM4Py): Bridging the Ga…
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…
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…
Open-source process mining provides many algorithms for the analysis of event data which could be used to analyze mainstream processes (e.g., O2C, P2P, CRM). However, compared to commercial tools, they lack the performance and struggle to…
Process mining enables business owners to discover and analyze their actual processes using event data that are widely available in information systems. Event data contain detailed information which is incredibly valuable for providing…
Process mining techniques such as process discovery and conformance checking provide insights into actual processes by analyzing event data that are widely available in information systems. These data are very valuable, but often contain…
pm4py is a process mining library for Python implementing several process mining (PM) artifacts and algorithms. It also offers methods to integrate PM with large language models (LLMs). This paper examines how the current paradigms of PM on…
www.processmining-software.com is a dedicated website for process mining software comparison and was developed to give practitioners and researchers an overview of commercial tools available on the market. Based on literature review and…
The most commonly used open-source process mining software tools today are ProM and PM4Py, written in Java and Python, respectively. Such high-level, often interpreted, programming languages trade off performance with memory safety and…
A large amount of data is produced every second from modern information systems such as mobile devices, the world wide web, Internet of Things, social media, etc. Analysis and mining of this massive data requires a lot of advanced tools and…
Process mining is a new emerging research trend over the last decade which focuses on analyzing the processes using event log and data. The raising integration of information systems for the operation of business processes provides the…
The recomputability and reproducibility of results from scientific software requires access to both the source code and all associated input and output data. However, the full collection of these resources often does not accompany the key…
Python is rapidly becoming the lingua franca of machine learning and scientific computing. With the broad use of frameworks such as Numpy, SciPy, and TensorFlow, scientific computing and machine learning are seeing a productivity boost on…
The capability of process mining techniques in providing extensive knowledge and insights into business processes has been widely acknowledged. Process mining techniques support discovering process models as well as analyzing process…
Process mining (PM) aims to construct, from event logs, process maps that can help discover, automate, improve, and monitor organizational processes. Robotic process automation (RPA) uses software robots to perform some tasks usually…
Object-centric process mining provides a more holistic view of processes where we analyze processes with multiple case notions. However, most object-centric process mining techniques consider the whole event log rather than the comparison…
Process mining techniques including process discovery, conformance checking, and process enhancement provide extensive knowledge about processes. Discovering running processes and deviations as well as detecting performance problems and…
Process mining represents an important field in BPM and data mining research. Recently, it has gained importance also for practitioners: more and more companies are creating business process intelligence solutions. The evaluation of process…
Smarter applications are making better use of the insights gleaned from data, having an impact on every industry and research discipline. At the core of this revolution lies the tools and the methods that are driving it, from processing the…
Process Mining is a branch of Data Science that aims to extract process-related information from event data contained in information systems, that is steadily increasing in amount. Many algorithms, and a general-purpose open source…
Process mining provides techniques to improve the performance and compliance of operational processes. Although sometimes the term "workflow mining" is used, the application in the context of Workflow Management (WFM) and Business Process…