Measurement and Computation of Profile Similarity of Workflow Nets Based on Behavioral Relation Matrix

Mimi Wang, Zhijun Ding, Guanjun Liu, Changjun Jiang, Mengchu Zhou

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

This paper focuses on the behavior similarity of workflow nets (WF-nets). The similarity of two WF-nets reflects their consistent degree in behaviors. It explores the behavioral relations of subsets of transitions based on the interleaving semantics, and more accurate relations are defined than the existing work. Therefore, a more accurate similarity of two WF-nets (in their behaviors) can be obtained than that in the existing work that usually do not consider the loop and complex correspondence. By refining the interleaving relation in a behavioral profile into six types, this paper proposes the notion of a relation profile based on behavioral profile. Based on the relation profile of a WF-net, behavioral relation matrix can be constructed. Additionally, we refine the complex correspondence and generate a group of behavioral relation submatrices from the behavioral relation matrix. By using them we present a new formula to measure the behavior similarity of two WF-nets. Finally, examples illustrate that our method can measure the similarity degree more accurately.

Original languageEnglish (US)
Article number8419090
Pages (from-to)3628-3645
Number of pages18
JournalIEEE Transactions on Systems, Man, and Cybernetics: Systems
Volume50
Issue number10
DOIs
StatePublished - Oct 2020
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Software
  • Control and Systems Engineering
  • Human-Computer Interaction
  • Computer Science Applications
  • Electrical and Electronic Engineering

Keywords

  • Behavioral relation matrix
  • complex correspondence
  • loop
  • similarity
  • workflow nets (WF-nets)

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