Process Profiling based Synthetic Event Log Generation

2019-09-19
ESGIN, EREN
Karagöz, Pınar
The goal of process mining is to discover the process behavior from the runtime information of process executions. Having labeled process logs is crucial for process mining research. However, real life event logs at process-aware information systems are mostly partially assigned to case identifiers, known as unlabeled event log problem. As a remedy to labeled data need in process mining research, we propose an approach to generate synthetic event logs according to the provided process profile, which outlines the activity vocabulary and structure of the corresponding business process. We evaluate the performance of our prototypical implementation in term of compatible log generation under varying parameter setting complexities.

Suggestions

Extracting process hierarchies by multi-sequence alignment adaptations
Esgin, Eren; Karagöz, Pınar (2021-01-01)
Process mining is an active research area that provides a wide range of automated process discovery, conformance checking and process enhancement solutions by extracting process information from event logs. With the emerge of new shared economy models and system architectures, monolithic perspective of process mining, i.e. a single process within a single organisation, is evolved towards cross-organisational business processes. The results can be used to form new collaboration among the organisations and sh...
A Hybrid Approach to Process Mining: Finding Immediate Successors of a Process by Using From-To Chart
Esgin, Eren; Karagöz, Pınar (2009-12-15)
Process mining is a branch of data mining that aims to discover process model from the event logs. In this study, we propose a hybrid approach to process mining in such a way that, "from-to chart" is used as the front-end to monitor the transitions among activities of a realistic event log. Another novelty of this study is developed evaluation metrics, which are used for finding immediate successors in order to convert these raw relations into dependency/frequency graph.
Process Maintenance through Component-Process Replacement
Manzer, Ayesha; Doğru, Ali Hikmet (2006-03-01)
An enterprise is represented by its process model that is constructed by the integration of smaller processes corresponding to value-added contributors. Replacing the sub-processes can modify the super-process. Component processes are represented in task systems in order to discover how process attributes will be preserved after integration. This approach is especially versatile if virtual enterprises are formed over the Internet through integrating the published processes of core competencies. The virtuall...
An approach for decentralized process modeling
Turetken, Oktay; Demirörs, Onur (2007-05-20)
This paper describes a method for organizations to perform process modeling in a decentralized and concurrent manner. The approach is based on the idea that modeling organizations' processes can be performed by individuals actually performing the processes. Instead of having a central and devoted group of people to analyze, understand, model and improve processes, real performers are held responsible to model and improve their own processes concurrently. The paper also summarizes the lessons learned by appl...
Generating performance improvement suggestions by using cross organizational process mining
Yılmaz, Onur; Karagöz, Pınar (null; 2015-12-10)
Process mining is a relatively young and developing research area with the main idea of discovering, monitoring and improving processes by extracting information from event logs. With the increase of cloud computing and shared infrastructures, event logs of multiple organizations are available for analysis where cross-organizational process mining stands with the opportunity for organizations learning from each other. The approach proposed in this study mines process models of organizations and calculates p...
Citation Formats
E. ESGIN and P. Karagöz, “Process Profiling based Synthetic Event Log Generation,” 2019, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/36298.