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Process mining is an area of research that supports discovering information about business processes from their execution event logs. The increasing amount of event logs in organizations challenges current process mining techniques, which…

数据库 · 计算机科学 2022-02-10 Amin Jalali

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…

人工智能 · 计算机科学 2025-02-04 Nikita Shaimov , Irina Lomazova , Alexey Mitsyuk

Process mining techniques enable organizations to analyze business process execution traces in order to identify opportunities for improving their operational performance. Oftentimes, such execution traces contain private information. For…

密码学与安全 · 计算机科学 2020-12-04 Gamal Elkoumy , Alisa Pankova , Marlon Dumas

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…

软件工程 · 计算机科学 2019-09-16 B. Kamala

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…

数据库 · 计算机科学 2019-08-01 Alessandro Berti

Process mining is a multi-purpose tool enabling organizations to improve their processes. One of the primary purposes of process mining is finding the root causes of performance or compliance problems in processes. The usual way of doing so…

密码学与安全 · 计算机科学 2019-09-02 Mahnaz Sadat Qafari , Wil van der Aalst

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…

数据库 · 计算机科学 2022-04-11 Marco Pegoraro , Merih Seran Uysal , Wil M. P. van der Aalst

The applicability of process mining techniques hinges on the availability of event logs capturing the execution of a business process. In some use cases, particularly those involving customer-facing processes, these event logs may contain…

密码学与安全 · 计算机科学 2021-08-31 Gamal Elkoumy , Alisa Pankova , Marlon Dumas

Process mining involves discovering, monitoring, and improving real processes by extracting knowledge from event logs in information systems. Process mining has become an important topic in recent years, as evidenced by a growing number of…

软件工程 · 计算机科学 2021-04-01 Sabah Al-Fedaghi

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…

数据库 · 计算机科学 2025-03-28 Ali Suleiman , Gamal Kassem

Anonymization of event logs facilitates process mining while protecting sensitive information of process stakeholders. Existing techniques, however, focus on the privatization of the control-flow. Other process perspectives, such as roles,…

数据库 · 计算机科学 2023-05-02 Ryan Hildebrant , Stephan A. Fahrenkrog-Petersen , Matthias Weidlich , Shangping Ren

Process mining allows analysts to exploit logs of historical executions of business processes to extract insights regarding the actual performance of these processes. One of the most widely studied process mining operations is automated…

In the contemporary business landscape, collaboration across multiple organizations offers a multitude of opportunities, including reduced operational costs, enhanced performance, and accelerated technological advancement. The application…

分布式、并行与集群计算 · 计算机科学 2024-10-08 Valerio Goretti , Davide Basile , Luca Barbaro , Claudio Di Ciccio

Inter-organizational business processes involve multiple independent organizations collaborating to achieve mutual interests. Process mining techniques have the potential to allow these organizations to enhance operational efficiency,…

分布式、并行与集群计算 · 计算机科学 2024-10-08 Valerio Goretti , Davide Basile , Luca Barbaro , Claudio Di Ciccio

Recently, information systems like ERP, CRM and WFM record different business events or activities in a log named as event log. Process mining aims at extracting information from event logs to capture business process as it is being…

软件工程 · 计算机科学 2015-07-22 Saiqa Aleem , Luiz Fernando Capretz , Faheem Ahmed

Process mining techniques enable organizations to gain insights into their business processes through the analysis of execution records (event logs) stored by information systems. While most process mining efforts focus on…

分布式、并行与集群计算 · 计算机科学 2026-02-05 Davide Basile , Valerio Goretti , Luca Barbaro , Hajo A. Reijers , Claudio Di Ciccio

Enterprise information systems allow companies to maintain detailed records of their business process executions. These records can be extracted in the form of event logs, which capture the execution of activities across multiple instances…

软件工程 · 计算机科学 2021-05-14 Adriano Augusto , Marlon Dumas , Marcello La Rosa

One of the most valuable assets of an organization is its organizational data. The analysis and mining of this potential hidden treasure can lead to much added-value for the organization. Process mining is an emerging area that can be…

软件工程 · 计算机科学 2016-07-05 Asef Pourmasoumi , Ebrahim Bagheri

Process mining methods allow analysts to use logs of historical executions of business processes in order to gain knowledge about the actual behavior of these processes. One of the most widely studied process mining operations is automated…

软件工程 · 计算机科学 2018-06-11 Fabrizio Maria Maggi , Andrea Marrella , Fredrik Milani , Allar Soo , Silva Kasela

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…

数据库 · 计算机科学 2022-11-02 Bianka Bakullari , Wil M. P. van der Aalst
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