Abstract
With the successful development of efficient algorithms for Frequent Subgraph Mining (FSM), this paper extends the scope of subgraph mining by proposing Vertex Unique labelled Subgraph Mining (VULSM). VULSM has a focus on the local properties of a graph and does not require external parameters such as the support threshold used in frequent pattern mining. There are many applications where the mining of VULS is significant, the application considered in this paper is error prediction with respect to sheet metal forming. More specifically this paper presents a formalism for VULSM and an algorithm, the Right-most Extension VULS Mining (REVULSM) algorithm, which identifies all VULS in a given graph. The performance of REVULSM is evaluated using a real world sheet metal forming application. The experimental results demonstrate that all VULS (Vertex Unique Labelled Subgraphs) can be effectively identified.
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Acknowledgments
The research leading to the results presented in this paper has received fund- ing from the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement number 266208.
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Yu, W., Coenen, F., Zito, M., Salhi, S.E. (2013). Vertex Unique Labelled Subgraph Mining. In: Bramer, M., Petridis, M. (eds) Research and Development in Intelligent Systems XXX. SGAI 2013. Springer, Cham. https://doi.org/10.1007/978-3-319-02621-3_2
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DOI: https://doi.org/10.1007/978-3-319-02621-3_2
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