基于邻域安全压缩的动态图增量子图匹配算法

针对目前最先进的增量子图匹配算法Symbi中的索引结构DCS中存在的信息冗余问题，提出了一种新的索引结构CDCS（compressed dynamic candidate space），并提出了CDCS的更新算法INCCDCS来动态维护CDCS索引结构和匹配结果，最后提出了动态图的增量子图匹配算法CSymbi。该方法通过引入邻域信息约束，在构建和更新辅助结构的过程中过滤候选集，提高算法的求解效率。最后，在Netflow和LSBench数据集上进行验证，相较于现有方法，候选节点数量最高可以删减56%，候选边数量最高可以删减62%，有效缩减了计算空间并提高了算法的求解效率。

Incremental subgraph matching algorithm based on neighborhood safe compression on dynamic graph

Aiming at the problem of information redundancy in the index structure DCS in Symbi, the most advanced incremental subgraph matching algorithm, this paper proposed a new index structure CDCS, and proposed the CDCS update algorithm INCCDCS to the CDCS index structure and dynamically maintained matching results, and finally proposed an incremental subgraph matching algorithm CSymbi for dynamic graphs. By introducing neighborhood information constraints, the method filtered candidate sets during the process of constructing and updating auxiliary structures, and improved the solution efficiency of the algorithm. Finally, it was verified on the Netflow dataset and LSBench dataset. Compared with the existing methods, the number of candidate nodes can be reduced by up to 56%, and the number of candidate edges can be reduced by up to 62%, which effectively reduces the calculation space and improves the algorithm, solution efficiency.