Abstract
This paper studies the following problem: given a pair of business process models, determine which elements in one model are related to which elements in the other model. This problem arises in the context of merging different versions or variants of a business process model or when comparing business process models in order to display their similarities and differences. The paper investigates two approaches to this alignment problem: one based purely on lexical matching of pairs of elements and another based on error-correcting graph matching. Using a set of models taken from real-life scenarios, the paper empirically shows that graph matching techniques yield a significantly higher precision than pure lexical matching, while achieving comparable recall.
Original language | English |
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Title of host publication | Proceedings of the 13th IEEE International Enterprise Distributed Object Computing Conference EDOC conference, Auckland |
Place of Publication | Piscataway, NJ |
Publisher | IEEE Computer Society |
Pages | 45-53 |
ISBN (Print) | 978-0-7695-3785-6 |
DOIs | |
Publication status | Published - 2009 |
Event | 13th IEEE International Enterprise Distributed Object Computing Conference (EDOC 2009) - Auckland, New Zealand Duration: 1 Sep 2009 → 4 Sep 2009 Conference number: 13 |
Conference
Conference | 13th IEEE International Enterprise Distributed Object Computing Conference (EDOC 2009) |
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Abbreviated title | EDOC 2009 |
Country/Territory | New Zealand |
City | Auckland |
Period | 1/09/09 → 4/09/09 |