SymmPi: Exploiting Symmetry Removal for Fast Subgraph Matching

被引:0
作者
Wang, Yujiang [1 ,2 ,3 ,4 ]
Cao, Ying [1 ,2 ,3 ,4 ]
Zhang, Zhaobo [1 ,2 ,3 ,4 ]
Yuan, Pingpeng [1 ,2 ,3 ,4 ]
Jin, Hai [1 ,2 ,3 ,4 ]
机构
[1] Natl Engn Res Ctr Big Data Technol & Syst, Wuhan, Peoples R China
[2] Serv Comp Technol & Syst Lab, Wuhan, Peoples R China
[3] Cluster & Grid Comp Lab, Wuhan 430074, Peoples R China
[4] Huazhong Univ Sci & Technol, Sch Comp Sci & Technol, Wuhan, Peoples R China
基金
中国国家自然科学基金;
关键词
Subgraph matching; Axisymmetry; Automorphism; Symmetry breaking; ALGORITHM;
D O I
10.1007/s41019-024-00271-w
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Symmetry, a phenomenon of self-similarity, is common in many networks, which often incurs a lot of redundant accesses and computations, even duplicate results when executing graph matching tasks. Many approaches (e.g. symmetry-breaking methods) try to disrupt symmetry by translating symmetry into restrictions and then imposing restrictions on the exploration order. However, the restrictions are finer-grained. If the pattern graph is complex, more restrictions are generated from symmetry breaking methods, thus complicating the exploration process and degrading the performance. Here, we present novel SymmPi, which exploits symmetry removal for fast graph matching. SymmPi first identifies the coarse-grained axisymmetric subgraphs of the given pattern graphs instead of finer relationships. If a pattern graph is not axisymmetric, SymmPi will remove some of its edges until axisymmetric subgraphs are found. Thus, the original pattern graph is transformed to a set of axisymmetric subgraphs plus some edges. Then, SymmPi finds the matches of the axisymmetric subgraph and extends these matches to the original pattern graphs by permuting the matches with additional checks. Our experiments on both directed and undirected graphs, demonstrate that SymmPi achieves a significant performance improvement over the state-of-the-art undirected and directed graph matching methods and systems.
引用
收藏
页码:230 / 245
页数:16
相关论文
共 50 条
[41]   Subgraph Matching with Diversity Handling and Its Applications to PCB Placement [J].
Chen, Chuandong ;
Lin, Haiming ;
Su, Miaodi ;
He, Huan ;
Chen, Jianli ;
Zhu, Ziran .
2024 INTERNATIONAL SYMPOSIUM OF ELECTRONICS DESIGN AUTOMATION, ISEDA 2024, 2024, :468-473
[42]   Subgraph Matching over Graph Federation [J].
Yuan, Ye ;
Ma, Delong ;
Wen, Zhenyu ;
Zhang, Zhiwei ;
Wang, Guoren .
PROCEEDINGS OF THE VLDB ENDOWMENT, 2021, 15 (03) :437-450
[43]   A Subgraph Learning Method for Graph Matching [J].
Chuang, Chen ;
Ya, Wang ;
Jia Wenwu .
LASER & OPTOELECTRONICS PROGRESS, 2020, 57 (06)
[44]   10X Faster Subgraph Matching: Dual Matching Networks with Interleaved Diffusion Attention [J].
Thanh Toan Nguyen ;
Quang Duc Nguyen ;
Ren, Zhao ;
Jo, Jun ;
Quoc Viet Hung Nguyen ;
Thanh Tam Nguyen .
2023 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, IJCNN, 2023,
[45]   Efficient Subgraph Matching: Harmonizing Dynamic Programming, Adaptive Matching Order, and Failing Set Together [J].
Han, Myoungji ;
Kim, Hyunjoon ;
Gu, Geonmo ;
Park, Kunsoo ;
Han, Wook-Shin .
SIGMOD '19: PROCEEDINGS OF THE 2019 INTERNATIONAL CONFERENCE ON MANAGEMENT OF DATA, 2019, :1429-1446
[46]   Fast Local Subgraph Counting [J].
Li, Qiyan ;
Yu, Jeffrey Xu .
PROCEEDINGS OF THE VLDB ENDOWMENT, 2024, 17 (08) :1967-1980
[47]   ASM: Adaptive Subgraph Matching via Efficient Compression and Label Filter [J].
Chai, Yanfeng ;
Li, Jiashu ;
Zhang, Qiang ;
Ge, Jiake ;
Wang, Xin .
WEB AND BIG DATA. APWEB-WAIM 2024 INTERNATIONAL WORKSHOPS, KGMA 2024, SEMIBDMA 2024, MADM 2024, AIEDM 2024 AND STBDM 2024, 2025, 2246 :30-42
[48]   An efficient pruning method for subgraph matching in large-scale graphs [J].
Moayed, Hojjat ;
Mansoori, Eghbal G. ;
Moosavi, Mohammad R. .
JOURNAL OF SUPERCOMPUTING, 2023, 79 (10) :10511-10532
[49]   Reinforcement Learning Based Query Vertex Ordering Model for Subgraph Matching [J].
Wang, Hanchen ;
Zhang, Ying ;
Qin, Lu ;
Wang, Wei ;
Zhang, Wenjie ;
Lin, Xuemin .
2022 IEEE 38TH INTERNATIONAL CONFERENCE ON DATA ENGINEERING (ICDE 2022), 2022, :245-258
[50]   EXPLORING A SUBGRAPH MATCHING APPROACH FOR EXTRACTING BIOLOGICAL EVENTS FROM LITERATURE [J].
Liu, Haibin ;
Keselj, Vlado ;
Blouin, Christian .
COMPUTATIONAL INTELLIGENCE, 2014, 30 (03) :600-635