Wasserstein Graph Distance Based on L1–Approximated Tree Edit Distance between Weisfeiler–Lehman Subtrees
Authors: Zhongxi Fang, Jianming Huang, Xun Su, Hiroyuki Kasai
AAAI 2023 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We conduct two types of experiments: metric validation and graph classification experiments. In the metric validation experiments, we demonstrate the effectiveness of the WWLS as a metric. In the graph classification experiments, we confirm the adaptability of the metric to graph classification, which represents one of its diverse applications. |
| Researcher Affiliation | Academia | Zhongxi Fang1, Jianming Huang1, Xun Su1, Hiroyuki Kasai1,2 1 Department of Computer Science and Communications Engineering, FSE Graduate School, Waseda University 2 Department of Communications and Computer Engineering, FSE School, Waseda University |
| Pseudocode | Yes | Algorithm 1: Enumerating all types of complete subtrees: DFSWL(G, h, v, d). Algorithm 2: Computing the WWLS distance. |
| Open Source Code | Yes | Source code: https://github.com/Fzx-oss/WWLS. |
| Open Datasets | Yes | We use TUD benchmark datasets, specifically selecting ten frequently used datasets, which can be grouped into two categories: (1) Bioinformatics datasets, including MUTAG, PTC-MR, COX2, ENZYMES, PROTEINS, NCI1, and BZR; and (2) Social network datasets, including IMDBB, IMDB-M, and COLLAB. |
| Dataset Splits | Yes | We employ a commonly used evaluation method for graph kernels (Morris et al. 2020), randomly splitting the data into a training set (90%) and a test set (10%), with a portion of the training set reserved for validation to tune the parameters. |
| Hardware Specification | Yes | The heavy processing parts of WWL and WWLS are written in C++, and we run programs on mac OS Monterey, Intel(R) Core(TM) i5-7360U CPU @ 2.30GHz. |
| Software Dependencies | No | The paper mentions C++ as the programming language and macOS Monterey as the operating system but does not provide specific version numbers for compilers, libraries, or other software dependencies. |
| Experiment Setup | Yes | The parameters of the WWLS are set as follows: we adjust the iteration number h within {2, 3} for the bioinformatics datasets and h = 1 for the social datasets due to their large node degrees; we adjust the parameter γ of Eq. (9) within {10 4, 10 3, . . . , 10 1}; and we adjust the regularization parameter C of SVM within {10 3, 10 2, . . . , 103}. |