Repo for Multidisciplinary Undergraduate Research Conference (MURC) 2024

data.csv

Data_Vis.ipynb

1. L. Chang, X. Feng, X. Lin, L. Qin, W. Zhang, and D. Ouyang, ‘Speeding up ged verification for graph similarity search’, in 2020 IEEE 36th International Conference on Data Engineering (ICDE), Apr. 2020, pp. 793–804. doi: 10.1109/ICDE48307.2020.00074.

2. W. Guo and J. Uhlmann, ‘Metric search for rank list compatibility matching with applications’. arXiv, Aug. 10, 2023. doi: 10.48550/arXiv.2303.11174.

3. J. Uhlmann and M. R. Zuniga, ‘The cascading metric tree’. arXiv, Dec. 20, 2021. doi: 10.48550/arXiv.2112.10900.

4. D. B. Blumenthal, S. Bougleux, J. Gamper, and L. Brun, ‘Gedlib: a c library for graph edit distance computation’, in Graph-Based Representations in Pattern Recognition, D. Conte, J.-Y. Ramel, and P. Foggia, Eds., in Lecture Notes in Computer Science. Cham: Springer International Publishing, 2019, pp. 14–24. doi: 10.1007/978-3-030-20081-7_2.

5. Z. Abu-Aisheh, R. Raveaux, and J.-Y. Ramel, ‘A graph database repository and performance evaluation metrics for graph edit distance’, in Graph-Based Representations in Pattern Recognition, C.-L. Liu, B. Luo, W. G. Kropatsch, and J. Cheng, Eds., in Lecture Notes in Computer Science. Cham: Springer International Publishing, 2015, pp. 138–147. doi: 10.1007/978-3-319-18224-7_14.

6. K. Riesen, A. Fischer, and H. Bunke, ‘Computing upper and lower bounds of graph edit distance in cubic time’, in Artificial Neural Networks in Pattern Recognition, N. El Gayar, F. Schwenker, and C. Suen, Eds., Cham: Springer International Publishing, 2014, pp. 129–140. doi: 10.1007/978-3-319-11656-3_12.

Wenqi Marshall Guo

[email protected]

report.md

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