The DOI matches its Crossref record; 24 of the 24 references it cites were found in a registry or an index.
Shortest-Path Kernels on Graphs
Abstract
Data mining algorithms are facing the challenge to deal with an increasing number of complex objects. For graph data, a whole toolbox of data mining algorithms becomes available by defining a kernel function on instances of graphs. Graph kernels based on walks, subtrees and cycles in graphs have been proposed so far. As a general problem, these kernels are either computationally expensive or limited in their expressiveness. We try to overcome this problem by defining expressive graph kernels which are based on paths. As the computation of all paths and longest paths in a graph is NP-hard, we propose graph kernels based on shortest paths. These kernels are computable in polynomial time, retain expressivity and are still positive definite. In experiments on classification of graph models of proteins, our shortest-path kernels show significantly higher classification accuracy than walk-based kernels.
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Cites
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Cited by
A Comprehensive Survey of Graph Embedding: Problems, Techniques, and Applications
Cai, H., Zheng, V. W., & Chang, K. C.-C. (2018) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2018.2807452 · Cited by 2,034
TUDataset: A collection of benchmark datasets for learning with graphs
Morris, C., Kriege, N. M., Bause, F., Kersting, K., Mutzel, P., & Neumann, M. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2007.08663 · Cited by 281
Kang, U., Tong, H., & Sun, J. (2012) · Proceedings of the 2012 SIAM International Conference on Data Mining · doi:10.1137/1.9781611972825.71 · Cited by 127
Rossi, L., Torsello, A., & Hancock, E. R. (2015) · Physical Review E · doi:10.1103/physreve.91.022815 · Cited by 46
Metadata
- Authors
- Borgwardt, K. M., & Kriegel, H.
- Venue
- Fifth IEEE International Conference on Data Mining (ICDM'05)
- Publisher
- IEEE
- Published
- 2006-01-05
- Pages
- 74-81
- ISSN
- 1550-4786 (ISSN-L)
- OpenAlex
- W2147286743
- Cited by
- 837
- References
- 24
- FWCI
- 10.74
- Type
- conference paper
- Language
- en
- Open access
- closed
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