TY - JOUR
T1 - Measurement and Computation of Profile Similarity of Workflow Nets Based on Behavioral Relation Matrix
AU - Wang, Mimi
AU - Ding, Zhijun
AU - Liu, Guanjun
AU - Jiang, Changjun
AU - Zhou, Mengchu
N1 - Funding Information:
Manuscript received December 20, 2017; revised March 14, 2018 and May 14, 2018; accepted June 28, 2018. Date of publication July 24, 2018; date of current version September 16, 2020. This work was supported in part by the Shanghai Science and Technology Innovation Action Plan Project under Grant 16511100900, and in part by the National Natural Science Foundation of China under Grant 61332008 and Grant 61672381. This paper was recommended by Associate Editor M. K. Tiwari. (Corresponding author: Changjun Jiang.) M. Wang, Z. Ding, G. Liu, and C. Jiang are with the Department of Computer Science and Engineering, Tongji University, Shanghai 201804, China, also with the Key Laboratory of Embedded System and Service Computing (Tongji University), Ministry of Education, Shanghai 201804, China, and also with the Shanghai Electronic Transactions and Information Service Collaborative Innovation Center, Tongji University, Shanghai 201804, China (e-mail: wangmimi2013@hotmail.com; dingzj@tongji.edu.cn; liuguanjun@tongji.edu.cn; cjjiang@tongji.edu.cn).
Publisher Copyright:
© 2013 IEEE.
PY - 2020/10
Y1 - 2020/10
N2 - 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.
AB - 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.
KW - Behavioral relation matrix
KW - complex correspondence
KW - loop
KW - similarity
KW - workflow nets (WF-nets)
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U2 - 10.1109/TSMC.2018.2852652
DO - 10.1109/TSMC.2018.2852652
M3 - Article
AN - SCOPUS:85050644958
SN - 2168-2216
VL - 50
SP - 3628
EP - 3645
JO - IEEE Transactions on Systems, Man, and Cybernetics: Systems
JF - IEEE Transactions on Systems, Man, and Cybernetics: Systems
IS - 10
M1 - 8419090
ER -