{"id":13481433,"url":"https://github.com/nlskrg/optimal_assignment_kernels","last_synced_at":"2025-03-27T12:30:49.488Z","repository":{"id":217670899,"uuid":"110851381","full_name":"nlskrg/optimal_assignment_kernels","owner":"nlskrg","description":"Source code for the paper \"On Valid Optimal Assignment Kernels and Applications to Graph Classification\", Nils M. Kriege, Pierre-Louis Giscard, Richard C. 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Kriege, Pierre-Louis Giscard, Richard C. Wilson, NIPS 2016.\n\n## Usage\nThe graph kernels contained in this package can be computed via a command line interface. Run the shell script `kkernel` to see a list of all available kernels and parameters.\n\n### Example\nThe following command computes the Weisfeiler-Lehman optimal assignment kernel with 0 to 4 refinement steps for the data set ENZYMES:\n```\n./kkernel -d ENZYMES wloa -h 0,1,2,3,4\n```\nFor each value of `h` the kernel matrix is computed and stored in the directory `gram` using the [LIBSVM](https://www.csie.ntu.edu.tw/~cjlin/libsvm/) file format.\n\n## Building from source\nRun `ant` to build `kgraph.jar` from source. \n\n## Data sets\nThe repository contains the data set ENZYMES only. Further data sets are available from the website [Benchmark Data Sets for Graph Kernels](http://graphkernels.cs.tu-dortmund.de). Please note that in our experimental comparison the edge labels, if present, were ignored. In order to reproduce the published results, please delete the files `DS_edge_labels.txt`, where `DS` is the name of the data set.\n\n## Terms and conditions\nWhen using our code please cite:\n\n\t@InCollection{NIPS2016_6166,\n\t  title                    = {On Valid Optimal Assignment Kernels and Applications to Graph Classification},\n\t  author                   = {Kriege, Nils M. and Giscard, Pierre-Louis and Wilson, Richard},\n\t  booktitle                = {Advances in Neural Information Processing Systems 29},\n\t  publisher                = {Curran Associates, Inc.},\n\t  year                     = {2016},\n\t  editor                   = {D. D. Lee and M. Sugiyama and U. V. Luxburg and I. Guyon and R. Garnett},\n\t  pages                    = {1623--1631}\n\t}\n\n## Contact information\nIf you have any questions, please contact [Nils Kriege](https://ls11-www.cs.tu-dortmund.de/staff/kriege).\n\n## Links\nA Matlab implementation of the Weisfeiler-Lehman optimal assignment kernel is available from [Matlab File Exchange](http://de.mathworks.com/matlabcentral/fileexchange/64711-weisfeiler-lehman-optimal-assignment-kernel).\n\n","funding_links":[],"categories":["Graph Kernels"],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnlskrg%2Foptimal_assignment_kernels","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fnlskrg%2Foptimal_assignment_kernels","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnlskrg%2Foptimal_assignment_kernels/lists"}