PathLAD+: An Improved Exact Algorithm for Subgraph Isomorphism Problem
Authors: Yiyuan Wang, Chenghou Jin, Shaowei Cai, Qingwei Lin
IJCAI 2023 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Experimental results on a broad range of real-world benchmarks show that our proposed algorithm performs better than state-of-the-art algorithms for the SIP. |
| Researcher Affiliation | Collaboration | Yiyuan Wang1,2 , Chenghou Jin3 , Shaowei Cai4,5, and Qingwei Lin6 1School of Computer Science and Information Technology, Northeast Normal University, China 2Key Laboratory of Applied Statistics of MOE, Northeast Normal University, Changchun, China 3Computer School, Beijing Information Science and Technology University, Beijing, China 4State Key Laboratory of Computer Science, Institute of Software, Chinese Academy of Sciences, Beijing, China 5School of Computer Science and Technology, University of Chinese Academy of Sciences, China 6Microsoft Research, China |
| Pseudocode | Yes | Algorithm 1 Path LAD+ Algorithm 2 Search SIP |
| Open Source Code | Yes | Our source code is publicly available at github3. |
| Open Datasets | Yes | For our experiments, we select all used instances from [Kraiczy and Mc Creesh, 2021; Liu et al., 2022] which can also download from the website1. (Footnote 1 provides the URL: http://liris.cnrs.fr/csolnon/SIP.html) |
| Dataset Splits | No | The paper uses benchmarks and instances to evaluate performance but does not specify traditional train/validation/test dataset splits. |
| Hardware Specification | Yes | All the algorithms are run on Intel(R) Xeon(R) Platinum 8260 CPU @ 2.40GHz 512GB RAM under Cent OS 7.9. |
| Software Dependencies | No | Our proposed algorithm and four competitors are all implemented in C++ and compiled by g++ with -O3 option. (A specific version number for g++ is not provided.) |
| Experiment Setup | Yes | According to our preliminary experiments, parameters max tries, β1, and β2 are set to 1000, 0.85, and 0.8, respectively. |