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基于对称破坏的子图同构约束求解算法

Constraint satisfaction algorithm for subgraph isomorphism with symmetry breaking
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摘要 为避免子图同构问题求解中重复解的产生,提高子图同构问题的约束求解效率,提出一种基于对称破坏的子图同构约束求解算法。基于解的对称破坏思想,改进自同构检测过程,通过置换群操作生成对称破坏字典序约束,构建子图同构问题的一种约束满足问题(CSP)模型,结合CSP的回溯算法对其求解。实验结果表明,该算法有效减少了对重复解的搜索,与传统算法相比明显提高了搜索效率。 To avoid the generation of repeated solutions and improve the efficiency of constraint solving in subgraph isomorphism problem,a constraint solving algorithm for solving subgraph isomorphism based on symmetric breaking was proposed.Based on the symmetry breaking method,the automorphism detection process was improved and a CSP model of the subgraph isomorphism problem was constructed by symmetry breaking lexicographic order constraint which was generated by the permutation group operation,and it was solved using CSP backtracking algorithm.Experimental results show that the proposed algorithm effectively reduces the search for repeated solutions and significantly improves the search efficiency compared with the traditional algorithms.
作者 徐周波 梁轩瑜 刘华东 戴瑀君 XU Zhou-bo;LIANG Xuan-yu;LIU Hua-dong;DAI Yu-jun(Guangxi Key Laboratory of Trusted Software,Guilin University of Electronic Technology,Guilin 541004,China;School of Mechanical and Electrical Engineering,Guilin University of Electronic Technology,Guilin 541004,China)
出处 《计算机工程与设计》 北大核心 2020年第2期397-401,共5页 Computer Engineering and Design
基金 国家自然科学基金项目(61762027、U1501252) 广西自然科学基金项目(2017GXNSFAA198172)
关键词 子图同构 约束满足问题 对称性破坏 自同构 置换群 subgraph isomorphism constraint satisfaction problem symmetry breaking automorphism permutation group
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  • 1Microsoft Academic Search. Explore researchers' cooperating network.[2009-12-01 J.[2014-11-20]. http://academic. research. microsoft. com/VisualExplorer.
  • 2Brynielsson J, Hogberg J, Kaati L, et al. Detecting social positions using simulation[C]//Proc of 2010 Int Conf on Advances in Social Networks Analysis and Mining (ASONAM). Alamitos, CA: IEEE, 2010: 48-55.
  • 3Palantir. Products Built for A Purpose.[2004-01-01].[2014-11-20]. https://www.palantir.com/.
  • 4Malewicz G, Austern M H, Bik A J C, et al, Pregel , A system for large-scale graph processing[C]//Proc of the 2010 ACM SIGMOD Int Conf on Management of Data. New York: ACM, 2010: 135-146.
  • 5Sarwat M, Elnikety S, He Y, et al. Horton: Online query execution engine for large distributed graphs[C]//Proc of the 28th IEEE Int Conf on Data Engineering (ICDE J. Alamitos, CA: IEEE, 2012: 1289-1292.
  • 6Low y, Gonzalez J, Kyrola A, et al. Graphlab , A new framework for parallel machine learning[C]//Proc of the 26th Conf on Uncertainty in Artificial Intelligence (UA]). Oregon, USA: AUAI, 2010.
  • 7Michael R G, David S J. Computers and intractability: A guide to the theory of NP-completeness[R]. New York: W. H. Freeman Company, 1979.
  • 8Christmas W J, Kittler J, Petrou M. Structural matching in computer vision using probabilistic relaxation[J]. Pattern Analysis and Machine Intelligence, 1995, 17(8): 749-764.
  • 9Ullmann J R. An algorithm for subgraph isomorphism[J]. Journal of the ACM (JACM), 1976,23(1): 31-42.
  • 10Cordelia L P, Foggia r. Sansone C, et al. A (sub) graph isomorphism algorithm for matching large graphs[J]. IEEE Trans on Pattern Analysis and Machine Intelligence, 2004, 26(10): 1367-1372.

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