Abstract
A mechanism is presented to classify (predict) the values associated with vertices in a given unlabelled graph or network. The proposed mechanism is founded on the concept of Vertex Unique Labelled Subgraphs (VULS). Two algorithms are presented. The first, the minimal Right-most Extension VULS Mining (minREVULSM) algorithm, is used to identify all minimal VULS in a given graph or nework. The second, the Match-Voting algorithm, is used to achieve the desired VULS based classification (prediction). The reported experimental evaluation demonstrates that by using the minimal VULS concept good results can be obtained in the context of a sheet metal forming application used for evaluation purposes.
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References
Cafuta, G., Mole, N., Tok, B.: An enhanced displacement adjustment method: Springback and thinning compensation. Materials and Design 40, 476–487 (2012)
Firat, M., Kaftanoglu, B., Eser, O.: Sheet metal forming analyses with an emphasis on the springback deformation. Journal of Materials Processing Technology 196(1-3), 135–148 (2008)
Jeswiet, J., Micari, F., Hirt, G., Bramley, A., Allwood, J., Duflou, J.: Asymmetric single point incremental forming of sheet metal. CIRP Annals Manufacturing Technology 54(2), 88–114 (2005)
Liu, W., Liang, Z., Huang, T., Chen, Y., Lian, J.: Process optimal ccontrol of sheet metal forming springback based on evolutionary strategy. In: 7th World Congress on Intelligent Control and Automation, WCICA 2008, pp. 7940–7945 (June 2008)
Nasrollahi, V., Arezoo, B.: Prediction of springback in sheet metal components with holes on the bending area, using experiments, finite element and neural networks. Materials and Design 36, 331–336 (2012)
Salhi, S., Coenen, F., Dixon, C., Khan, M.: Identification of correlations between 3d surfaces using data mining techniques: Predicting springback in sheet metal forming. In: Proceedings Proc. AI 2012, pp. 391–404. Springer, Cambridge (2012)
Yan, X., Han, J.: gSpan: Graph-based substructure pattern mining. In: Proceedings of the 2002 International Conference on Data Mining, p. 721 (2002)
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Yu, W., Coenen, F., Zito, M., El Salhi, S. (2013). Vertex Unique Labelled Subgraph Mining for Vertex Label Classification. In: Motoda, H., Wu, Z., Cao, L., Zaiane, O., Yao, M., Wang, W. (eds) Advanced Data Mining and Applications. ADMA 2013. Lecture Notes in Computer Science(), vol 8346. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-53914-5_46
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DOI: https://doi.org/10.1007/978-3-642-53914-5_46
Publisher Name: Springer, Berlin, Heidelberg
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