桂林电子科技大学学报2026，Vol.46Issue(4)：348-353,371,7.DOI:10.16725/j.1673-808X.2023123
基于新过滤技术的子图匹配符号ADD算法
Symbolic ADD algorithm for subgraph matching based on new filtering techniques
摘要
Abstract
Subgraph matching is a fundamental NP-complete problem with broad applications in computer vision,data mining,and bioinformatics.To reduce redundant computations in subgraph matching,a novel algorithm named DDCSA is proposed by incorpo-rating a new filtering technique.To improve the pruning efficiency of candidate sets for query vertices,a compressed storage struc-ture is constructed by integrating the symbolic algebraic decision diagram(ADD)structure with the CS structure used in the DAF al-gorithm.In addition,a new candidate filtering technique,termed DDFilter,is developed by introducing k-field aggregation con-straints.Experimental results demonstrate that DDCSA significantly improves the efficiency of subgraph isomorphism computation compared with the DAF algorithm.关键词
图匹配问题/子图匹配/过滤技术/代数决策图(ADD)/辅助结构Key words
graph matching problem/subgraph matching/filtering technique/algebraic decision diagram(ADD)/auxiliary structure分类
信息技术与安全科学引用本文复制引用
王嘉鑫,徐周波,龙广兴..基于新过滤技术的子图匹配符号ADD算法[J].桂林电子科技大学学报,2026,46(4):348-353,371,7.基金项目
国家自然科学基金(61762027) （61762027）
