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Querying process models by behavior inclusion

  • Business processes are vital to managing organizations as they sustain a company's competitiveness. Consequently, these organizations maintain collections of hundreds or thousands of process models for streamlining working procedures and facilitating process implementation. Yet, the management of large process model collections requires effective searching capabilities. Recent research focused on similarity search of process models, but querying process models is still a largely open topic. This article presents an approach to querying process models that takes a process example as input and discovers all models that allow replaying the behavior of the query. To this end, we provide a notion of behavioral inclusion that is based on trace semantics and abstraction. Additional to deciding a match, a closeness score is provided that describes how well the behavior of the query is represented in the model and can be used for ranking. The article introduces the formal foundations of the approach and shows how they are applied to queryingBusiness processes are vital to managing organizations as they sustain a company's competitiveness. Consequently, these organizations maintain collections of hundreds or thousands of process models for streamlining working procedures and facilitating process implementation. Yet, the management of large process model collections requires effective searching capabilities. Recent research focused on similarity search of process models, but querying process models is still a largely open topic. This article presents an approach to querying process models that takes a process example as input and discovers all models that allow replaying the behavior of the query. To this end, we provide a notion of behavioral inclusion that is based on trace semantics and abstraction. Additional to deciding a match, a closeness score is provided that describes how well the behavior of the query is represented in the model and can be used for ranking. The article introduces the formal foundations of the approach and shows how they are applied to querying large process model collections. An experimental evaluation has been conducted that confirms the suitability of the solution as well as its applicability and scalability in practice.show moreshow less

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Metadaten
Author details:Matthias Kunze, Matthias Weidlich, Mathias WeskeORCiDGND
DOI:https://doi.org/10.1007/s10270-013-0389-6
ISSN:1619-1366
ISSN:1619-1374
Title of parent work (English):Software and systems modeling
Publisher:Springer
Place of publishing:Heidelberg
Publication type:Article
Language:English
Year of first publication:2015
Publication year:2015
Release date:2017/03/27
Tag:Behavioral querying; Process model repositories; Process model search; Trace inclusion
Volume:14
Issue:3
Number of pages:21
First page:1105
Last Page:1125
Organizational units:An-Institute / Hasso-Plattner-Institut für Digital Engineering gGmbH
Peer review:Referiert
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