Extracting process hierarchies by multi-sequence alignment adaptations

Date

2021-01-01

Author

Esgin, Eren
Karagöz, Pınar

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

285
views

0
downloads

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 share best practices, business knowledge or a common infrastructure. However, the variability across the cross-organisational process variants constitutes a challenge to deal with, especially at flexible environments. This paper demonstrates a quantitative approach to measure how similar organisations execute the same process. The approach is based on the multi-sequence alignment of dominant behaviour, which is a typical sequence of behaviour recurring at the process cases. Then process clusters are extracted in the form of process hierarchy according to the degree of process similarities. A novel feature of the proposed approach is that branching in process hierarchy reflects how organisations’ behaviours differ from each other. Additionally, common fragments at the aligned process variants within the same cluster pinpoint a functional inheritance or a shared process behaviour for the corresponding organisations. The proposed approach is applied on a real-life case and the comparison with previous alignment techniques reveals the advantages of the approach.

Subject Keywords

Cross-organisational business processes, dominant behaviour, Multi-sequence alignment, Process clustering, Process hierarchies

URI

https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85106471806&origin=inward
https://hdl.handle.net/11511/90894

Journal

Enterprise Information Systems

DOI

https://doi.org/10.1080/17517575.2021.1913239

Collections

Department of Computer Engineering, Article

Suggestions

OpenMETU
Core

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...
Recommendation generation for performance improvement by using cross-organizational process mining Yılmaz, Onur; Yarman Vural, Fatoş Tunay; Department of Computer Engineering (2015) Process mining is a relatively young and developing research area with the main idea of discovering, monitoring and improving processes by extracting information from the 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 calculat...
Process Profiling based Synthetic Event Log Generation ESGIN, EREN; Karagöz, Pınar (2019-09-19) 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 outline...
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.
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...

Citation Formats

E. Esgin and P. Karagöz, “Extracting process hierarchies by multi-sequence alignment adaptations,” Enterprise Information Systems, pp. 0–0, 2021, Accessed: 00, 2021. [Online]. Available: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85106471806&origin=inward.