Graph Matching Algorithms for Business Process Model Similarity Search
By Remco M. Dijkman, Marlon Dumas, Luciano García-Bañuelos. International Conference on Business Process Management, 2009
428 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Computer Networks and Communications, Management Information Systems
View Paper: https://www.semanticscholar.org/paper/194b78a9d8655c9819d58ac4e5c1d9ed25852b75
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Pushmeet Kohli
- Yujia Li
- Yoshua Bengio
- William L. Hamilton
- Oriol Vinyals
- Ruslan Salakhutdinov
- Percy Liang
- Mohit Bansal
In Computer Networks and Communications
- Jan Mendling
- Pushmeet Kohli
- Wil M.P. van der Aalst
- Oriol Vinyals
- Chenjie Gu
- Thomas Dullien
- Frank Puhlmann
- Fabian Friedrich
In Management Information Systems
- Jan Mendling
- Wil M.P. van der Aalst
- Oriol Vinyals
- Frank Puhlmann
- Fabian Friedrich
- Manfred Reichert
- Bernd Weber
- Wil van der Aalst
Citations in the corpus
- Graph Matching Networks for Learning the Similarity of Graph Structured Objects (2019, background): “Graph edit distance is naturally a measure of similarity between graphs and has many applications in graph similarity search (Dijkman et al., 2009; Zeng et al., 2009; Gao et al., 2010).”
- Business Process Management: A Comprehensive Survey (2013, methodology): “The paper “Graph matching algorithms for business process model similarity search” [56] presented at the same conference was tagged with the use case select model from collection (SelM) since the paper presents an approach to rank process models in a repository based on some input model.”
- Process Model Generation from Natural Language Text (2011, methodology): “Afterwards a greedy graph matching heuristic [33] is employed to create pairs of nodes and edges.”