A Short Survey on Process Model Similarity

Dijkman, Remco M.; Dumas, Marlon; García‐Bañuelos, Luciano; Kunze, Matthias; Leopold, Henrik; Mendling, Jan; Uba, Reina; Weidlich, Matthias; Weske, Mathias; Yan, Zhiqiang

doi:10.1007/978-3-642-36926-1_34

Cited by 22 publications

(5 citation statements)

References 31 publications

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“…Most of them use natural language processing techniques for eliciting label similarity (Smirnov et al 2010). In (Dijkman et al 2013), several metrics for determining similarity of two labels such as edit distance or semantic similarity has been investigated.…”

Section: Related Workmentioning

confidence: 99%

Mining variable fragments from process event logs

2016

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Many peer-organizations are now using processaware information systems for managing their organizational processes. Most of these peer-organizations have shared processes, which include many commonalities and some degrees of variability. Analyzing and mining the commonalities of these processes can have many benefits from the reusability point of view. In this paper, we propose an approach for extracting common process fragments from a collection of event logs. To this end, we first analyze the process fragment literature from a theoretical point of view, based on which we present a new process fragment definition, called morphological fragments to support composability and flexibility. Then we propose a novel algorithm for extracting such morphological fragments directly from process event logs. This algorithm is capable of eliciting common fragments from a family of processes that may not have been executed within the same application/organization. We also propose supporting algorithms for detecting and categorizing morphological fragments for the purpose of reusability. Our empirical studies show that our approach is able to support reusability and flexibility in process fragment identification.

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Section: Related Workmentioning

confidence: 99%

Mining variable fragments from process event logs

2016

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“…Actually, there are different similarity measures that are analysed in [32]. Some specifications are expressed in a form of query, then processes which hold those specifications are ranked based on their similarity with the given query [33]. Whatever the form of similarity measuring is, common approaches with minor changes can be applied for different objectives. To calculate the similarity of processes, methods mostly use either structural or behavioural similarity.…”

Section: Related Workmentioning

confidence: 99%

“…Some specifications are expressed in a form of query, then processes which hold those specifications are ranked based on their similarity with the given query [33]. Whatever the form of similarity measuring is, common approaches with minor changes can be applied for different objectives.…”

Section: Related Workmentioning

confidence: 99%

“…Since most approaches for process similarity are either structural or behavioural, they suffer from exponential complexity, so the abstractions are proposed in [33] in which the order of execution of two activities is considered. Indexing techniques can be applied to implement searching for all similar processes to a query process, more efficient.…”

Section: Related Workmentioning

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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“…Service recommendation [9,10] can be also applied in the context of activity recommendation. Behavioral abstractions such as trace adjacency [5,36] and weak order relations [19,34] provide a means to compare process behavior [15,22,16]. These notions are applied, e.g., for identifying connections between actions [30] comparable to our notion of activity neighborhood.…”

Section: Related Workmentioning

confidence: 99%

Mining Event Logs to Assist the Development of Executable Process Variants

Chân

Yongsiriwit

Gaaloul

et al. 2014

Lecture Notes in Computer Science

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International audienceDeveloping process variants has been proven as a principle task to flexibly adapt a business process model to different markets. Con-temporary research on variant development has focused on conceptual process models. However, process models do not always exist, even when process logs are available in information systems. Moreover, process logs are often more detailed than process models and reflect more closely to the behavior of the process. In this paper, we propose an activity rec-ommendation approach that takes into account process logs for assisting the development of executable process variants. To this end, we define a notion of neighborhood context for each activity based on logs, which captures order constraints between activities with their occurrence fre-quency. The similarity of the neighborhood context between activities provides us then with a basis to recommend activities during the process of creating a new process model. The approach has been implemented as a plug-in for ProM. Furthermore, we conducted experiments on a large collection of process logs. The results indicate that our approach is feasible and applicable in real use cases

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A Short Survey on Process Model Similarity

Abstract: Process model similarity has developed into a prolific field of investigation. This paper summarizes the research after the CAISE 2008 paper on this topic. We identify categories of problems and provide an outlook on future directions.

Cited by 22 publications

References 31 publications

Mining variable fragments from process event logs

Mining variable fragments from process event logs

Data‐driven business process similarity

Mining Event Logs to Assist the Development of Executable Process Variants

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