Towards Multi-perspective Process Model Similarity Matching

Baumann, Michael Heinrich; Baumann, Michaela; Schönig, Stefan; Jablonski, Stefan

doi:10.1007/978-3-662-44860-1_2

Cited by 8 publications

(5 citation statements)

References 11 publications

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“…As future work, activities with different granularities can be taken into account. These activities can be identified by considering their data accesses [11]. Also we are working on calculating the similarity of different data objects.…”

Section: Discussionmentioning

confidence: 99%

“…Similar to many approaches, Dijkman et al [26] used string edit distance to compute node similarity. Baumann et al [11] involved actors, data objects, and their order of appearing in the model to match activities based on their labels. The proposed mapping is partial and injective.…”

Section: Related Workmentioning

confidence: 99%

“…when modellers use different vocabulary. So it is useless or even impossible to use only label matching to analyse sets of activities [11].…”

Section: Related Workmentioning

confidence: 99%

“…In addition, there may be meaningless labels which do not convey useful information about the desired activity. Moreover, different words or synonyms may be used to describe the same activity [11]. So there may be an activity with multiple labels.…”

Section: Introductionmentioning

confidence: 99%

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Data‐driven business process similarity

Amiri

Koupaee

2017

IET softw.

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Although measuring the similarity of business processes based on activity labels, structural and behavioural factors can be effective, defining inexact and incomplete labels and the existence of multiple labels for similar activities cause challenges for determining similar processes. Recent attempts to consider data in business process management and the support of data modelling in business process standards have led to the creation of multiple business models with data access. In this study, a method considering data for measuring business process similarity is presented in which first the similarity of activities is measured according to their structures and behaviours in a process and also their data access. Then based on the similarity of activities, the similarity of processes is determined using the proposed algorithm.

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Section: Discussionmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

“…when modellers use different vocabulary. So it is useless or even impossible to use only label matching to analyse sets of activities [11].…”

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Data‐driven business process similarity

Amiri

Koupaee

2017

IET softw.

View full text Add to dashboard Cite

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“…The similarity of business process models (mainly in the form of imperative models) was investigated in many papers (e.g., [29], [30], [31], [32]), often in the context of a model repository. Analysis of model similarity can be useful before adding a new process model to the model repository to avoid process model duplication.…”

Section: Related Workmentioning

confidence: 99%

Imperative vs. Declarative Modeling of Industrial Process. The Case Study of the Longwall Shearer Operation

et al. 2023

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Process modeling is an important and necessary step for further analysis and monitoring of industrial processes. In the process modeling two main paradigms exist, namely imperative and declarative ones. In our work, we analyzed information potential of these model paradigms regarding to conformance checking task of real life industrial process -longwall shearer operation carried out in an underground coal mine. The objective of our work was an analysis of selected imperative and declarative models to discover which approach is more appropriate from a practical point of view, taking into consideration criteria formulated by the domain expert. The first novelty of our work rely on real life industrial sensor data analysis and creation of event log with heuristic approach for case ID identification and labeling with expert rules. In parallel, we created prescribed process models. As representatives of imperative and declarative languages, we have selected the Petri nets and Declare models, respectively. We created two Petri nets (with Inductive and Heuristic Miner) and seven declarative models differ in restriction power. Due to the better description of the ideal cycle, to the further analysis and conformance checking task, we selected the Petri net created by Heuristic Miner. After the process model creation, we compared selected Petri net with Declare models using the natural language approach and constraints hierarchy. Based on created similarity measures, we choose one declarative model to conformance checking task and comparison with Petri net due to formulated quantitative and qualitative criteria. As main artifact in the conformance checking task, we used obtained real event log. Evaluation of the created models indicates that in the case of the longwall shearer operation monitoring, the declarative model better captures the necessary information to decision-makers than the Petri net, thus being more appropriate for practical use.

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