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Published in:
2014 | OriginalPaper | Chapter
TAGER: Transition-Labeled Graph Edit Distance Similarity Measure on Process Models
Authors : Zixuan Wang, Lijie Wen, Jianmin Wang, Shuhao Wang
Published in: On the Move to Meaningful Internet Systems: OTM 2014 Conferences
Publisher: Springer Berlin Heidelberg
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Although several approaches have been proposed to compute the similarity between process models, they have various limitations. We propose an approach named TAGER (
T
ransition-l
A
beled
G
raph
E
dit distance similarity Measu
R
e) to compute the similarity based on the edit distance between coverability graphs. As the coverability graph represents the behavior of a Petri net well, TAGER, based on it, has a high precise computation. Besides, the T-labeled graphs (an isomorphic graph of the coverability graph) of models are independent, so TAGER can be used as the index for searching process models in a repository. We evaluate TAGER from efficiency and quality perspectives. The results show that TAGER meets all the seven criteria and the distance metric requirement that a good similarity algorithm should have. TAGER also balances the efficiency and precision well.