Name
Abstract | ||
|---|---|---|
Although several approaches have been proposed to compute the similarity between process models, they have various limitations. We propose an approach named TAGER (Transition-lAbeled Graph Edit distance similarity MeasuRe) 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. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1007/978-3-662-45563-0_11 | Lecture Notes in Computer Science |
Keywords | Field | DocType |
Business Process Model,Transition-labeled Graph,Edit Distance,Behavioral Similarity | Edit distance,Combinatorics,Petri net,Similarity measure,Graph isomorphism,Process modeling,Metric (mathematics),Theoretical computer science,Business process modeling,Mathematics,Computation | Conference |
Volume | ISSN | Citations |
8841 | 0302-9743 | 2 |
PageRank | References | Authors |
0.41 | 8 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zixuan Wang | 1 | 9 | 12.65 |
| Lijie Wen | 2 | 452 | 44.34 |
| Jianmin Wang | 3 | 2446 | 156.05 |
| Shuhao Wang | 4 | 5 | 1.92 |